Social Network Analysis

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

The Statistics of Canada

Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

A Survey of Device-to-Device Communications: Research Issues and Challenges

Limited energy of the sensors is one of the key issues towards realizing a reliable wireless sensor network (WSN), which can survive under the emerging WSN applications. A promising method for conserving the energy of these sensors can be implemented by applying a sleep-wake scheduling while distributing the data gathering and sensing tasks to a dominating set of awake sensors while the other nodes are in a sleep mode. Producing the maximum possible number of such disjoint dominating sets, called the domatic partition problem in unit disk graphs, can further prolong the network lifetime. This problem becomes challenging when the initial energy of the nodes varies from one to another. In this paper, we introduce multiple local search algorithms that can improve the total lifetime of WSNs consisting of nodes with varying initial energy. We discuss the performance of the existing dominating set algorithm and introduce three more algorithms which can be applied on multiple disjoint dominating sets with nodes having varying initial energy. We discuss the efficiency of each of the algorithms through extensive simulations.

Dominating Set Algorithms for Wireless Sensor Networks Survivability

Interference minimization while maintaining a target system sum rate by sharing radio resources among cellular user equipments (UEs) and device-to-device (D2D) pairs is an important research question in long term evolution (LTE) and beyond (4G and 5G). Total system sum rate of a cellular network can be improved if cellular UEs and D2D pairs share resource blocks. However, some sharing can also decrease the sum rate and increase the system interference. Considering this observation, we address two types of assignments (fair and restricted) in resource allocation for the interference minimization resource allocation problem. We propose a two-phase resource allocation algorithm for both fair and restricted assignments, where our objective is to minimize the system interference and at the same time, maintaining a target system sum rate. In the phase-I of our proposed algorithm, a weighted bipartite matching algorithm is used to minimize the interference and get a feasible initial solution. In some cases, we can decrease the interference introduced in phase-I of our algorithm. Therefore, in the phase-II, local search techniques are used to improve the solution. We compare the fair assignment of our proposed algorithms with a two-phase auction-based fair and interference aware resource allocation algorithm (TAFIRA), which addresses the same research problem. As well as, we compare the restricted assignment of our proposed algorithm with a minimum knapsack-based interference resource allocation algorithm (MIKIRA). We prove that the MIKIRA fails to provide feasible solutions in most of the cases. We also show that the performance ratio of the TAFIRA can be unbounded in the worst case. Moreover, in some cases, TAFIRA cannot provide any solution to the problem though the solutions exist, whereas our proposed algorithms always provide a solution whenever the solution exists. We perform extensive simulations of the algorithms and find that in all the cases, our proposed algorithm outperforms a number of state-of-the-art algorithms.

Interference Minimization in D2D Communication Underlaying Cellular Networks

Vehicular crowdsensing aims to utilize the plethora of onboard sensors and resources on smart vehicles to gather sensing data in a large coverage area. Recruitment algorithms aim to select participants within a crowdsensing network such that the most sensing data is obtained for the lowest possible cost. In this paper, we consider two such existing recruitment problems for vehicular crowdsensing and propose several heuristics. We also show that existing algorithms to solve these problems can be arbitrarily bad in the worst case. We also compare our algorithms with both optimal solutions (returned by mixed integer programs) as well as existing heuristics. Performance evaluations on our algorithms show that our algorithms outperform existing algorithms and obtain near optimal solutions.

Improved Recruitment Algorithms for Vehicular Crowdsensing Networks

An Auction Mechanism for Profit Maximization of Peer-to-Peer Energy Trading in Smart Grids

In a device to device (D2D) communication underlaying cellular network, total system sum rate (capacity) can be improved if cellular user equipment’s (UEs) and D2D pairs share resource blocks (RBs). We consider an optimization problem where the objective is to maximize the total sum rate of the system by sharing RBs among cellular UEs and D2D pairs while maintaining the quality of service requirements. We consider three approaches depending on the degree of sharing i.e., “One to One Sharing” , “One to Many Sharing” , and “Many to Many Sharing” . Most of the existing algorithms consider that sharing of RBs can only improve the total system sum rate. However, sharing of RBs between a cellular UE and a D2D pair can also decrease the total system sum rate. Considering this observation, we propose an algorithm based on the weighted bipartite matching algorithm which avoids such sharing and maximize the total system sum rate for the “One to One Sharing” approach. Moreover, We propose resource allocation algorithms for “One to Many Sharing” and “Many to Many Sharing” with a target to maximize the system capacity and also provide the analysis of the proposed algorithms. Through simulations, we find that our proposed algorithms outperform the existing algorithms in terms of maximizing total system sum rate. Our proposed algorithms also perform better in terms of total interference introduced due to the sharing of RBs among cellular UEs and D2D pairs.

Salimur Choudhury

Papers

Dominating Set Algorithms for Wireless Sensor Networks Survivability

Interference Minimization in D2D Communication Underlaying Cellular Networks

Improved Recruitment Algorithms for Vehicular Crowdsensing Networks

An Auction Mechanism for Profit Maximization of Peer-to-Peer Energy Trading in Smart Grids

System Capacity Maximization With Efficient Resource Allocation Algorithms in D2D Communication