Session 1

Caching

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Achieving Freshness in Single/Multi-User Caching of Dynamic Content over the Wireless Edge

Bahman Abolhassani (Ohio State University, USA), John Tadrous (Gonzaga University, USA), and Atilla Eryilmaz (Ohio State University, USA),

2
Existing content caching mechanisms are predominantly geared towards easy-access of content that is static once created. However, numerous applications, such as news and dynamic sources with time-varying states, generate ‘dynamic’ content where new updates replace previous versions. This motivates us in this work to study the freshness-driven caching algorithm for dynamic content, which accounts for the changing nature of data content. In particular, we provide new models and analyses of the average operational cost both for the single-user and multi-user scenarios. In both scenarios, we characterize the performance of the optimal solution and develop algorithms to select the content and the update rate that the user(s) must employ to have low-cost access to fresh content. Moreover, our work reveals new and easy-to-calculate key metrics for quantifying the caching value of dynamic content in terms of their refresh rates, popularity, number of users in the multi-user group, and the fetching and update costs associated with the optimal decisions. We compare the proposed freshness-driven caching strategies with benchmark caching strategies like cache the most popular content. Results demonstrate that freshness-driven caching strategies considerably enhance the utilization of the edge caches with possibly orders-of-magnitude cost reduction. Furthermore, our investigations reveals that multi-user scenario, benefiting from the multicasting property of wireless service to update the cache content, can be cost effective compared to single user caching, as the number of users increases.

Augmenting Multiple-Transmitter Coded Caching using Popularity Knowledge at the Transmitters

Berksan Serbetci (EURECOM, France), Eleftherios Lampiris (Technical University of Berlin, Germany), Thrasyvoulos Spyropoulos (EURECOM, France), and Petros Elia (EURECOM, France),

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The work presents a new way of exploiting non-uniform file popularity in caching networks. Focusing on the interference channel with cache-enabled transmitters and receivers, we show how non-uniform file popularity can be used to accelerate the impact of transmitter-side data redundancy in coded caching. This approach is motivated by the recent discovery that under realistic file-size constraints, having content appear in multiple transmitters can boost multiplicatively the speed-up factor attributed to coded caching. We formulate the problem through an optimization algorithm, which seeks to optimize the number of transmitters each file is cached at, as a function of that file’s popularity. Part of the optimization effort involves a biconvex problem; such problems are traditionally solved by heuristic Alternate Convex Search methods that generally do not guarantee the global optimum. To avoid this, we follow a more involved path which includes the design of a new search algorithm that exploits the properties of the caching problem itself. The overall optimization algorithm provably achieves the globally optimal solution, and does so with a complexity that scales as a polynomial function of the logarithm of the size of the file catalog. In the end, the optimal transmitter-side cache placement yields multiplicative speedup factors over traditional multi-transmitter coded caching algorithms.

RetroRenting: An Online Policy for Service Caching at the Edge

Lakshmi Narayana V S Ch, Sharayu Moharir and Nikhil Karamchandani (Indian Institute of Technology-Bombay, India)

0
For both architectures, we will propose system level models and evaluate their performance gains w.r.t. the conventional cellular architecture of the Euclidean plane. We will analyze the network performance by explicitly deriving the distribution of the signal-to-noise and interference ratio experienced by typical network elements. For the mesh+vehicle multi-hop architecture, we will also show that if the density of IoT devices is large and the density of repositories scales with that of IoT devices, then the proposed architecture has a capacity scaling that outperforms that of the conventional mesh+cellular architecture, with a performance gain which is polynomial in the density.

Optimal Uncoded Placement and File Grouping Structure for Improved Coded Caching under Nonuniform Popularity

Yong Deng and Min Dong (Ontario Tech University, Canada)

2
This paper considers the caching design for coded caching under nonuniform file popularity. We investigate the optimal cache placement for the modified coded caching scheme (MCCS) recently proposed with an improved delivery strategy for rate reduction over the original coded caching scheme (CCS). We use the optimization framework for the cache placement problem to minimize the average delivery rate. Exploring several properties of the optimization problem and analyzing its structure, we obtain the file grouping structure under the optimal cache placement. We show that, regardless of file popularity, there are at most three file groups under the optimal cache placement. We further characterize the complete structure of the optimal cache placement and obtain the closed-form placement solution in these three possible file group cases. Following these, we develop a simple algorithm to obtain the final optimal cache placement solution, which only requires to compute a set of candidate solutions in closed-form. Simulation verifies the optimal solution produced by our algorithm. The optimal MCCS is shown to outperform existing schemes for both MCCS and CCS.

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Session 2

Learning and Decision making

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Incentive Mechanism Design for Federated Learning with Multi-Dimensional Private Information

Ningning Ding (Chinese University of Hong Kong, Hong Kong), Zhixuan Fang (Chinese University of Hong Kong, Hong Kong), and Jianwei Huang (Chinese University of Hong Kong, Hong Kong, Chinese University of Hong Kong-Shenzhen, China, and Shenzhen Institute of AI and Robotics for Society, China)

0
As an emerging machine learning technique, federated learning has received significant attention recently due to its promising performance in mitigating privacy risks and costs. In federated learning, the model training is distributed over users and coordinated by a central server. Users only need to send the most updated learning model parameters to the server without revealing their private data. While most of the existing work of federated learning focused on designing the learning algorithm to improve the training performance, the incentive issue for encouraging users’ participation is still under-explored. Such a fundamental issue can significantly affect the training efficiency, effectiveness, and even the practical operability of federated learning. This paper presents an analytical study on the server’s optimal incentive mechanism design, in the presence of users’ multi-dimensional private information including training cost and communication delay. Specifically, we consider a multi-dimensional contract-theoretic approach, with a key contribution of summarizing users’ multi-dimensional private information into a one-dimensional criterion that allows a complete order of users. We further perform the analysis in three different information scenarios to reveal the impact of the level of information asymmetry on server’s optimal strategy and minimum cost. We show that weakly incomplete information does not increase the server’s cost. However, the optimal mechanism design under strongly incomplete information is much more challenging, and it is not always optimal for the server to incentivize the group of users with the lowest training cost and delay to participate.

Optimal Decisions of a Rational Agent in the Presence of Biased Information Providers

Himaja Kesavareddigari and Atilla Eryilmaz (Ohio State University, USA)

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We consider information networks whereby multiple biased-information-providers (BIPs), e.g., media outlets/social network users/sensors, share reports of events with rational- information-consumers (RICs). Making the reasonable abstraction that an event can be reported as an answer to a logical statement, we model the input-output behavior of each BIP as a binary channel. For various reasons, some BIPs might share incorrect reports of the event. Moreover, each BIP is: ‘biased’ if it favors one of the two outcomes while reporting, or ‘unbiased’ if it favors neither outcome. Such biases occur in information/social networks due to differences in users’ characteristics/worldviews. We study the impact of the BIPs’ biases on an RIC’s choices while deducing the true information. Our work reveals that a “graph-blind” RIC looking for n BIPs among its neighbors, acts peculiarly in order to minimize its probability of making an error while deducing the true information. First, we establish the counter-intuitive fact that the RIC’s expected error is minimized by choosing BIPs that are fully-biased against the a-priori likely event. Then, we study the gains that fully-biased BIPs provide over unbiased BIPs when the error rates of their binary channels are equalized, for fair comparison, at some r > 0. Specifically, the unbiased-to-fully-biased ratio of the RIC’s expected error probabilities grows exponentially with the exponent n/2. This shows not only that fully-biased BIPs are preferable to unbiased or heterogeneously-biased BIPs, but also that the gains can be substantial for small r.

Socially Optimal Correlated Equilibrium in Class-Anonymous Offloading Game with Computing Access Points

Eric Jiang and Ben Liang (University of Toronto, Canada)

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We consider a multi-user mobile offloading network with multiple computing access points (CAPs). Each user has one task to be processed, and may choose to reduce the cost of processing the task by offloading it to a CAP or to a remote cloud server. Each user belongs to one of a fixed number of classes, which determines the distribution of their task parameters. We aim to produce an offloading decision that minimizes the expected social cost of the system, while giving selfish users an incentive to follow that decision. Towards that goal, we show that our system can be formulated as a class-anonymous game, and we derive the reduced form of this game to prove that a socially optimal correlated equilibrium (CE) can be computed in polynomial time and space with respect to the number of users. Like the Nash Equilibrium, the CE maintains the necessary conditions for stability in a system with rational and selfish users, while being much easier to compute for non-potential finite games. Simulation results demonstrate the superior results of our solution when compared with random mapping and an alternate means of computing a CE.

A false data injection attack on networked cyber-physical systems

Moulik Choraria (Indian Institute of Technology - Delhi, India), Arpan Chattopadhyay (Indian Institute of Technology - Delhi, India), Urbashi Mitra (University of Southern California, India), and Erik Strom (Chalmers University, Sweden)

0
Herein, design of false data injection attack on a distributed cyber-physical system is considered. A stochastic process with linear dynamics and Gaussian noise is measured by multiple agent nodes, each equipped with multiple sensors. The agent nodes form a multi-hop network among themselves. Each agent node computes an estimate of the process by using its sensor observation and messages obtained from neighboring nodes, via Kalman-consensus filtering. An external attacker, capable of arbitrarily manipulating the sensor observations of some or all agent nodes, injects errors into those sensor observations. The goal of the attacker is to steer the estimates at the agent nodes as close as possible to a pre-specified value, while respecting a constraint on the attack detection probability. To this end, a constrained optimization problem is formulated to find the optimal parameter values of a certain class of linear attacks. The parameters of linear attack are learnt on-line via a combination of two-timescale stochastic approximation and online stochastic gradient descent. Numerical results demonstrate the efficacy of the attack.

Online Crowd Learning with Heterogeneous Workers via Majority Voting

Chao Huang (Chinese University of Hong Kong, Hong Kong), Haoran Yu (Beijing Institute of Technology), Jianwei Huang (Chinese University of Hong Kong, Hong Kong, Chinese University of Hong Kong, Shenzhen, China, and Shenzhen Institute of AI and Robotics for Society, China), and Randall Berry (Northwestern University)

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UAVs moving on planned trajectories.

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Session 3

Scheduling, graphs, and stochastic geometry

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Non-clairvoyant Scheduling of Coflows

Akhil Bhimaraju (Indian Institute of Technology Madras, India), Debanuj Nayak (Indian Institute of Technology Gandhinagar, India), and Rahul Vaze (Tata Institute of Fundamental Research, Mumbai, India)

0
The coflow scheduling problem is considered: given an input/output switch with each port having a fixed capacity, find a scheduling algorithm that minimizes the weighted sum of the coflow completion times respecting the port capacities, where each flow of a coflow has a demand per input/output port, and coflow completion time is the finishing time of the last flow of the coflow. The objective of this paper is to present theoretical guarantees on approximating the sum of coflow completion time in the non-clairvoyant setting, where on a coflow arrival, only the number of flows, and their input-output port is revealed, while the critical demand volumes for each flow on the respective input-output port is unknown. The main result of this paper is to show that the proposed BlindFlow algorithm is 8p-approximate, where p is the largest number of input-output port pairs that a coflow uses. This result holds even in the online case, where coflows arrive over time and the scheduler has to use only causal information. Simulations reveal that the experimental performance of BlindFlow is far better than the theoretical guarantee.

Wireless queues in Poisson interference fields: the continuum between zero and infinite mobility

Nithin Ramesan and François Baccelli (University of Texas at Austin, USA)

0
This paper considers the time evolution of a queue that is placed in a Poisson point process of moving wireless interferers. The queue evolves according to an external arrival process and a time-varying service process that is a function of the SINR that it experiences. Static configurations of interferers result in infinite queue workload with positive probability. In contrast, a velocity-independent stability condition for the queue is established in the case where interferers possess any non-zero mobility that results in displacements that are both independent across interferers and with a distribution which is invariant to interferer positions. The proof leverages mixing properties of point processes under non-zero mobility. The effects of increasing mobility on statistical averages of queueing metrics are studied, and convex ordering tools are used to establish that faster moving interferers result in a queue workload that is dominated in the increasing convex sense by a queue workload resulting from slower interferers. As a corollary, it is shown that mean queue workload and mean delay improve as network mobility increases. It is shown that there is positive correlation between SINR level-crossing events at finitely separated time points. The notion of correlation between interference over time is made precise via an explicit correlation function. System behaviour is empirically analyzed using discrete event simulation and the impact of the mobility model on system level performance is evaluated.

Local Construction of Connected and Plane Spanning Subgraphs under Acyclic Redundancy

Steffen Böhmer, Lucas Böltz and Hannes Frey (University of Koblenz-Landau, Germany)

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Plane graphs play a major role for local routing and some other local network protocols in wireless communication. With such local algorithms each node requires information about its neighborhood only. It is assumed that nodes are deployed on the plane and each node knows its position in a given coordinate system. An arbitrary graph drawn on the plane can be transformed into a plane spanning subgraph by deleting edges. However, to assure connectivity at the same time some additional structural graph properties are required. Current graph classes that assure the existence of connected plane spanning subgraphs require assumptions, that are not very likely to hold for wireless network structures. In this work we develop the acyclic redundancy condition. This is a novel graph class with only one property that assures the existence of a connected plane spanning subgraph. Furthermore, we describe local algorithms that construct a connected plane spanning subgraph for graphs satisfying the acyclic redundancy condition. With numerical studies we confirm that the acyclic redundancy condition is a more realistic condition than existing graph classes that were required so far to construct connected plane spanning subgraphs.

A new strategy for the selection of communication technologies in VANETs with fully controllable vehicles.

Dorine Tabary, Sébastien Bindel, Frédéric Drouhin and Benoît Hilt (University of Haute Alsace, France

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Vehicular communications are laying the foundations for new research areas. Embedded systems within vehicles allow the management of information in movement situations. This article focuses on the choice of the communication technology used by the vehicles with controllable trajectories. The objective is to maximize the throughput, in the centralized way, provided by these vehicles. The study area is a map divided into zones. The choice of communication technologies depends on the crossing zone of the map. In the studied scenario, the vehicle paths and their communication technologies are defined according to this environment. The number of communication technologies usable in the same zone, c, may be restricted. The problem is first formulated as an optimization problem. The complexity of this problem is then proven as N P − hard and there is no possibility of constant factor approximation algorithmgenerally. Assuming c ≥ k, with k the number of controllable vehicles, the problem remains N P −hard, but a new polynomial time α-approximation algorithm is analyzed. The variable α is equal to (1 −1e) with e being the base of the natural logarithm. This ratio is the best possible, unless N P ⊆ DT IME(nloglog(n)).

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Session 4

Network Slicing and 5G

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Servicing Inelasticity, Leasing Resources and Pricing in 5G Networks

Apostolos Apostolaras (University of Thessaly and CERTH, Greece), Kostas Chounos (University of Thessaly and CERTH, Greece), Leandros Tassiulas (Yale University, USA), and Thanasis Korakis (University of Thessaly and CERTH, Greece)

0
We consider the problem for mobile network operators (MNOs) of leasing resources, servicing and pricing mobile users, in the context of 5G systems that facilitate the use of software-defined radio access network (SD-RAN) and network function virtualization (NFV) technologies. We study the case where the service capability of a MNO cannot satisfy the total users’ demand who are characterized by inelastic behavior against the servicing rate that they experience. The MNO addresses this temporal depletion of its resources and acquires dynamically, through leasing, additional resources from an infrastructure provider (InP) to adequately comply with its mobile users’ demand. We model and analyze the interactions among the MNO, and the users, as a Stackelberg game. To model users’ inelastic behavior, we use a sigmoid utility function. Furthermore, we show the optimal pricing decisions when MNO’s supplying capacity satisfies users’ demand. Given an excess on MNO’s supplying capacity, we employ the generalized r-Lambert function to determine the optimal pricing. When MNO’s supplying capacity is not ample, we determine, besides pricing, an approximation of the optimal amount of the additional resources to purchase, given a leasing cost imposed by the InP. An interesting finding shows that the amount of additional resources to be purchased can be larger than the MNO’s minimum capacity gap. Simulation and testbed experimentation validate the feasibility of the proposed pricing and leasing scheme and demonstrate its practical application.

Constrained Network Slicing Games: Achieving Service Guarantees and Network Efficiency

Jiaxiao Zheng (University of Texas at Austin, USA), Gustavo de Veciana (University of Texas at Austin, USA), and Albert Banchs (University Carlos III Madrid and IMDEA Networks, Spain),

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Network slicing is a key capability for next generation mobile networks. It enables one to cost effectively customize logical networks over a shared infrastructure. A critical component of network slicing is resource allocation, which needs to ensure that slices receive the resources needed to support their services while optimizing network efficiency. In this paper, we propose a novel approach to slice-based resource allocation named Guaranteed seRvice Efficient nETwork slicing (GREET). The underlying concept is to set up a constrained resource allocation game, where (i) slices unilaterally optimize their allocations to best meet their (dynamic) customer loads, while (ii) constraints are imposed to guarantee that, if they wish so, slices receive a pre-agreed share of the network resources. The resulting game is a variation of the well-known Fisher market, where slices are provided a budget to contend for network resources (as in a traditional Fisher market), but (unlike a Fisher market) prices are constrained for some resources to provide the desired guarantees. In this way, GREET combines the advantages of a share-based approach (high efficiency by flexible sharing) and reservation-based ones (which provide guarantees by assigning a fixed amount of resources). We characterize the Nash equilibrium, best response dynamics, and propose a practical slice strategy with provable convergence properties. Extensive simulations exhibit substantial improvements over network slicing state-of-the-art benchmarks.

Joint Scheduling of Low-Latency and Best-Effort Flows in 5G Wireless Networks

Tom Pijnappel (Eindhoven University of Technology, Netherlands), Sem Borst (Eindhoven University of Technology, Netherlands), and Philip Whiting (Macquarie University, Australia)

1
This survey presentation is based on join work with Chang Sik Choi (Qualcomm Research) and Gustavo de Veciana (UT Austin, ECE).

A Mechanism for Price Differentiation and Slicing in Wireless Networks

Mandar Datar (INRIA Sophia Antipolis Mediteranée and CERI/LIA-University of Avignon, France), Eitan Altman ((INRIA Sophia Antipolis - Mediteranée, CERI/LIA-University of Avignon and LINCS Lab Paris, France), Francesco De Pellegrini (CERI/LIA-University of Avignon, France), Rachid Elazouzi (CERI/LIA - University of Avignon, France), and Corinne Touati (INRIA Grenoble - Rhône-Alpes, France)

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Slicing has been introduced in 5G networks in order to deliver the higher degree of flexility and scalability required by future services. Slice tenants such as virtual wireless operators, service providers or smart-city services will be able to book a share of the infrastructure, possibly including storage, computing capacity and link bandwidth. However, 5G slicing is attractive for infrastructure providers as long as they are able to generate revenues, while at once satisfying the tenants’ competing and variable demands and coping with resources availability. This work proposes a flexible mechanism based on a multibidding scheme for 5G slice allocation. It is able to attain desirable fairness and efficiency figures in order to serve slice tenants and associated mobile users. Built on the notion of normalised Nash equilibrium, it is also provably overbooking- free even though the players’ bids are oblivious to infrastructure resources constraints. Also, it is compatible with standard radio access schedulers used in modern mobile networks. Finally, a practical algorithm is proposed to drive the system to the socially-optimal operating point via an online procedure rooted on a primal-dual distributed algorithm. Numerical simulations confirm the viability of the mechanism in terms of efficiency and fairness.

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Session 5

Age of Information

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Age-of-Information Bandits

Kavya Bhandari, Santosh Fatale, Urvidh Narula, Sharayu Moharir and Manjesh Kumar Hanawal (Indian Institute of Technology, Bombay, India)

0
The multi-hop architecture, which is referred to as mesh+vehicular, is based on mesh communications between IoT devices and short range communications between repositories located along the roads, again represented as Poisson lines, and vehicular gateways passing by, also represented as Poisson point processes on these lines.

Optimizing Timely Coverage in Communication Constrained Collaborative Sensing Systems

Jean Abou Rahal (University of Texas at Austin, USA), Gustavo de Veciana (University of Texas at Austin, USA), Takayuki Shimizu (Toyota Motor North America, USA), and Hongsheng Lu (Toyota Motor North America, USA)

1
We consider a collection of distributed sensor nodes periodically exchanging information to achieve real-time situational awareness in a communication constrained setting, e.g., collaborative sensing amongst vehicles to enable safety-critical decisions. Nodes may be both consumers and producers of sensed information. Consumers express interest in information about particular locations, e.g., obstructed regions and/or road intersections, whilst producers provide updates on what they are currently able to see. Accordingly, we introduce and explore optimizing trade-offs between the coverage and the space-time average of the “age” of the information available to consumers. We consider two settings that capture the fundamental character of the problem. The first addresses selecting a subset of producers which optimizes a weighted sum of the coverage and the average age given that producers provide updates at a fixed rate. The second addresses the minimization of the weighted average age achieved by a fixed subset of producers with possibly overlapping coverage by optimizing their update rates. The former is shown to be submodular and thus amenable to greedy optimization while the latter has a non-convex/non-concave cost function which is amenable to effective optimization using tools such as the Frank- Wolfe algorithm. Numerical results exhibit the benefits of context dependent optimization information exchanges among obstructed sensing nodes in a communication constrained environment.

Status Updates with Priorities: Lexicographic Optimality

Ali Maatouk (CentraleSupélec, France), Yin Sun (Auburn University, USA), Anthony Ephremides (University of Maryland, College Park, USA), and Mohamad Assaad (CentraleSupélec, France)

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In this paper, we consider a transmission scheduling problem, in which several streams of status update packets with diverse priority levels are sent through a shared channel to their destinations. We introduce a notion of Lexicographic age optimality, or simply lex-age-optimality, to evaluate the performance of multi-class status update policies. In particular, a lex-age-optimal scheduling policy first minimizes the Age of Information (AoI) metrics for high-priority streams, and then, within the set of optimal policies for high-priority streams, achieves the minimum AoI metrics for low-priority streams. We propose a new scheduling policy named Preemptive Priority, Maximum Age First, Last-Generated, First-Served (PP-MAF-LGFS), and prove that the PP-MAF-LGFS scheduling policy is lex-age-optimal in the single exponential server settings. This result holds (i) for minimizing any time-dependent, symmetric, and non-decreasing age penalty function; (ii) for minimizing any non-decreasing functional of the stochastic process formed by the age penalty function; and (iii) for the cases where different priority classes have distinct arrival traffic patterns, age penalty functions, and age penalty functionals. For example, the PP-MAF-LGFS scheduling policy is lex-age-optimal for minimizing the mean peak age of a high-priority stream and the time-average age of a low-priority stream. Numerical results are provided to illustrate our theoretical findings.

Average Age of Information for a Multi-Source M/M/1 Queueing Model with Packet Management and Self-Preemption in Service

Mohammad Moltafet (University of Oulu, Finland), Markus Leinonen (University of Oulu, Finland) and Marian Codreanu (Linkøping University, Sweden)

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We consider an M/M/1 status update system consisting of two independent sources and one server. We deriv the average age of information (AoI) of each source using the stochastic hybrid systems (SHS) technique under the following packet management with self-preemptive serving policy. The system can contain at most two packets with different source indexes at the same time, i.e., one packet under service and one packet in the queue. When the system is empty, any arriving packet immediately enters the server. When the server is busy at an arrival of a packet, the possible packet of the same source in the system (either waiting in the queue or being served) is replaced by the fresh packet. Numerical results illustrate the effectiveness of the proposed packet management with self-preemptive serving policy compared to several baseline policies.

Age of Information Aware UAV Network Selection

Man Hon Cheung (Chinese University of Hong Kong, Hong Kong)

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For the command and control in unmanned aerial vehicles (UAVs), it is important to limit the latency of the real-time status updates. Previously proposed network selection schemes mainly select the closest or the strongest-signal base station (BS) for data rate maximization, thus neglecting the BSs’ queueing and handover delays. In this paper, we aim to minimize the age of information (AoI) in both the network access and handover. Specifically, with the BS’ load and UAVs’ flight plan information, each UAV needs to choose between uncongested BSs for low-latency updates or BSs along its trajectory for less frequent handovers. As the UAVs’ decisions are coupled towards the BSs’ load, we formulate the UAVs’ interactions as a non- cooperative game, where each UAV aims to minimize its cost as the summation of the associated BSs’ average AoI and the handover penalties. We show that it is a potential game by characterizing its exact potential function. It leads to the design of a distributed BS association (DBA) algorithm, whose output is guaranteed to converge to a Nash equilibrium within a finite number of iterations. Simulation results show that the DBA scheme’s load-aware handover leads to a lower AoI cost than two benchmark schemes.

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Session 6

Network economics and Markets

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Entry and Investment in CBRS Shared Spectrum

Arnob Ghosh (Indian Institute of Technology - Delhi, India), and Randall Berry (Northwestern University, USA)

1
The Citizens Broadband Radio Service (CBRS) recently adopted in the U.S. enables commercial users to share spectrum with incumbent federal users. This sharing can be assisted by Environmental Sensing Capability operators (ESCs), that monitor the spectrum occupancy to determine when the use of the spectrum will not harm incumbents. An important aspect of the CBRS is that it enables two tiers of spectrum access by commercial users. The higher tier corresponds to a spectrum access (SA) firm that purchases a priority access license (PAL) in a competitive auction. The PAL holder obtains dedicated licensed access to a portion of the spectrum when the incumbent is not present. The lower tier, referred to as generalized Authorized Access (GAA), does not request a PAL and is similar to unlicensed access, in which multiple firms share a portion of the spectrum. Entry and investment in such a market introduces a number of new dimensions. Should an entrant bid for a PAL? How does the availability of a PAL impact their investment decisions? We develop a game-theoretic model to study these issues in which entrant SAs may bid in a PAL auction and decide on their investment levels and then compete downstream for customers.

Optimal Pricing in Finite Server Systems

Ashok Krishnan K S (Indian Institute of Science Bangalore, India), Chandramani Singh (Indian Institute of Science Bangalore, India), Siva Theja Maguluri (Georgia Institute of Technology, USA), and Parimal Parag (Indian Institute of Science Bangalore, India)

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We consider a system of K servers, where customers arrive according to a Poisson process, and have independent and identical (i.i.d.) exponential service times and i.i.d. valuations of the service. We consider the setting where customers leave when they find all servers busy. Service provider announces a price to an incoming customer, depending on the number of busy servers.

How Much to Share in Resource Pooling

Nithin Ramesan (University of Texas at Austin, USA), Sachin Nayak (Sony Corporation, Japan), and Rahul Vaze (Tata Institute of Fundamental Research, Mumbai, India)

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Resource pooling between two service providers, each having a fixed number of resources is considered. Each of the providers commit some of their resources to the common pool, and use the other providers’ resources (committed by it to the common pool) if available to service their clients if all of their own resources are completely occupied. Each such request requires a fixed payment to the other provider. The standard model of exponentially distributed occupancy time for each resource request is assumed. Assuming transferable utilities, Shapley value based inter-provider payoff keeps the coalition stable, and the problem is to find the optimal number of resources to commit to the common pool by each provider that maximizes the sum of the revenues of the two service providers. An exact solution is derived for the problem that depends on the prices charged by each provider to its clients. In case of equal prices, either full sharing or no sharing is shown to be optimal. Otherwise, the service provider with lower price commits all its resources, while the other provider commits resources depending on the solution of a recursive equation.

Optimal Partitioning of Spectrum Bands in Tiered Spectrum Access under Stochastic Market Models

Gourav Saha and Alhussein Abouzeid (Rensselaer Polytechnic institute, USA)

0
We consider the problem of partitioning an entire band into M channels of equal bandwidth, and then further assigning these M channels into P ≤ M licensed channels and M − P unlicensed channels. Licensed channels can be accessed both for licensed use and opportunistic use while unlicensed channels can be accessed only for opportunistic use. The access to licensed channels follows a tiered structure, where licensed use has a higher priority than opportunistic use. We address the following question in this paper. Given a market setup, what values of M and P maximize the net spectrum utilization of the entire bandwidth? This abstract problem is highly relevant in practical scenarios, e.g., in the context of partitioning the recently proposed Citizens Broadband Radio Service band. If M is too high (low), it may decrease (increase) spectrum utilization due to limited (wastage of) channel capacity. If P is too high (low), it will not incentivize the wireless operators who are primarily interested in licensed (unlicensed) channels to join the market. These trade-offs are captured in the optimization problem which is modeled as a two- stage Stackelberg game consisting of the regulator and the wireless operators. We design an algorithm to solve the Stackelberg game in order to find the optimal M and P. We use this algorithm to obtain interesting numerical results that suggest how the optimal values of M and P change with different market settings.

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Session 7

Wireless Resource allocation

Conference
12:01 AM — 11:59 PM EEST
Local
Jun 15 Mon, 5:01 PM — 4:59 PM EDT

Joint Optimization of Relaying Rate and Energy Consumption for Cooperative Mobile Edge Computing

Nilanjan Biswas, Seyed Hamed Mirghasemi and Luc Vandendorpe (Universite Catholique de Louvian, Belgium)

0
Mobile edge computing networks with energy constrained users, which do not have access to licensed spectrum, might face difficulty in completing delay sensitive computational tasks due to lack of proper offloading spectrum. This paper considers a mobile edge computing scenario in the context of cooperative communication, where an user (with no access to licensed spectrum) relays a licensed spectrum holder’s data to get access to the licensed spectrum for computation task offloading. We consider the relay to have a heavy computational task to complete by a given time duration. However, due to less computation power, the relay might not be able to meet the timeline. In this regard, the relay might offload partial computational task over the licensed spectrum to a more computationally powerful node, e.g., mobile edge computing server. The licensed spectrum holder might be interested in maximizing the relaying rate; whereas, the relay might want to minimize the total energy consumption for the task computation. We consider the relay partially offloading it’s computational task and formulate an optimization problem capturing two different interests for the licensed spectrum holder and the relay. In the optimization problem, we consider relevant constraints to make it more general. The optimization problem is observed to be non-convex. However, after analysis, we propose a less complex iterative algorithm. We observe that joint optimization provides a better trade-off between the relaying rate and the energy consumption at the WU, which is not observed for individual relaying rate maximization and energy consumption minimization.

Cross-layer communication over fading channels with adaptive decision feedback

Borna Sayedana (McGill University, Canada), Aditya Mahajan (McGill University, Canada), and Edmund Yeh (Northeastern University, USA)

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In this paper, cross-layer design of transmitting data packets over AWGN fading channel with adaptive decision feedback is considered. The transmitter decides the number of packets to transmit and the threshold of the decision feedback based on the queue length and the channel state. The transmit power is chosen such that the probability of error is below a pre- specified threshold. We model the system as a Markov decision process and use ideas from lattice theory to establish qualitative properties of optimal transmission strategies. In particular, we show that: (i) if the channel state remains the same and the number of packets in the queue increase, then the optimal policy either transmits more packets or uses a smaller decision feedback threshold or both; and (ii) if the number of packets in the queue remain the same and the channel quality deteriorates, then the optimal policy either transmits fewer packets or uses a larger threshold for the decision feedback or both. We also show under rate constraints that if the channel gains for all channel states are above a threshold, then the “or” in the above characterization can be replaced by “and”. Finally, we present a numerical example showing that adaptive decision feedback significantly improves the power-delay trade-off as compared with the case of no feedback.

Ergodic Capacity Performance of NOMA- SWIPT Aided IoT Relay Systems with Direct Link

Ashish Rauniyar (University of Oslo and Oslo Metropolitan University, Norway), Paal Engelstad (University of Oslo and Oslo Metropolitan University, Norway), and Olav N. Østerbø (Telenor Research, Norway)

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For the delay-tolerant transmission mode, ergodic capacity (EC) is an appropriate measure for the performance analysis of the system. In this paper, we investigate the EC and ergodic sum capacity (ESC) performance of cooperative non-orthogonal multiple access (NOMA) simultaneous wireless information and power transfer (SWIPT) aided Internet of Things (IoT) relay systems with direct links over the Rayleigh fading channels. To the best of our knowledge, there is no published literature that investigates the EC and ESC of the NOMA-SWIPT aided IoT relay systems with the direct link, in which one source or base station (BS) transmits symbol to two destination nodes through the direct link and with the help of EH based relay node. Specifically, we study the time switching (TS), and power splitting (PS) relaying architecture for increasing the spectral and energy-efficiency of the considered system. Analytical expressions for the EC and the ESC are mathematically derived and validated by the simulation results. Our results not only provide a thorough comparison of the TS and PS relaying EH architecture for the considered system model, but it also demonstrates that the ESC performance could be significantly improved through the optimal choice of the power splitting factor for PS relaying with NOMA compared to TS relaying with NOMA.

On the Optimal ARQ Distribution for Low-Latency Communication over Line-of-Sight Dominated Multi-Hop Networks

Jaya Goel and J Harshan (Indian Institute of Technology-Delhi, India)

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Multi-hop networks that are dominated by line- of-sight (LOS) wireless channels have gained traction in the recent past owing to the emergence of wireless networks based on unmanned aerial vehicles. One of the challenges in such vehicular networks is to design communication strategies to provide both ultra-reliability and low-latency features. Towards providing ultra-reliability against channel impairments, it is well known that automatic repeat request (ARQ) based decode-and- forward relaying is an effective strategy wherein each transmitter can be allotted an appropriate number of re-transmissions based on the LOS component of its forward link. However, in order to provide low-latency features, it is also known that multiple re-transmissions may not be a favorable choice as the total number of re-transmissions across the relays incurs significant delay in communicating the packet in the end-to-end network. Identifying this conflict introduced by the ARQ protocol, we investigate the optimal allocation of the number of ARQs at each link so as to minimize the packet-drop-probability at the destination subject to a sum constraint on the total number of ARQs allotted to all the nodes in the network. First, we prove a set of necessary and sufficient conditions on the optimal ARQ distribution, and then use these conditions to propose a low-complexity algorithm to solve the problem statement. Through extensive simulation results, we show that the proposed algorithm significantly reduces the computational complexity when compared to exhaustive search and yet recovers the optimal ARQ distribution.

Distributed Alpha-Fair Throughput Aggregation in Multi-RAT Wireless Networks

Ehsan Aryafar (Portland State University, USA) and Alireza Keshavarz-Haddad (Shiraz University, Iran)

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In the single-hop architecture, at any given time, a vehicle is assumed to communicate with a device selected at random in a domain centered at the vehicle. We will both consider the case where vehicles move on roads modeled by a Poisson line process and where vehicles are Poisson point processes on these roads, respectively, and the case where vehicles are

Session Chair

Not Needed — Asynchronous Q&A throughout the conference

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Session Opening-1

Welcome Talk

Conference
3:30 PM — 3:45 PM EEST
Local
Jun 16 Tue, 8:30 AM — 8:45 AM EDT

Welcome talk

Thanasis Korakis (University of Thessaly) – General Chair

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This talk does not have an abstract.

Session Chair

Thanasis Korakis (University of Thessaly) – General Chair

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Session Opening-2

Technical Program Opening and Best Paper Award Announcements

Conference
3:45 PM — 4:00 PM EEST
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Jun 16 Tue, 8:45 AM — 9:00 AM EDT

Technical Program Opening and Best Paper Award Announcements

Iordanis Koutsopoulos (Athens University of Economics and Business) -TPC Co-chair

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Session Chair

Iordanis Koutsopoulos (Athens University of Economics and Business) -TPC Co-chair

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Session Keynote-1

Keynote 1

Conference
4:15 PM — 5:30 PM EEST
Local
Jun 16 Tue, 9:15 AM — 10:30 AM EDT

Optimizing Information Freshness in Wireless Networks: From Theory to Practice

Eytan Modiano (Massachusetts Institute of Technology)

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Age of Information (AoI) is a recently proposed performance metric that captures the freshness of the information from the perspective of the application. AoI measures the time that elapsed from the moment that the most recently received packet was generated to the present time. In this talk, we explore the AoI optimization problem in wireless networks.
We start by considering a wireless network with a number of nodes transmitting information to a base station and develop low-complexity transmission scheduling policies that result in near-optimal AoI performance. We then extend our results to wireless networks under general interference constraints, and develop joint routing and scheduling schemes for minimizing AoI. Finally, we discuss implementation of our transmission scheduling policies using software defined radios.

Session Chair

Longbo Huang (Tsinghua University)

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