Summary The transformation of traditional networks is being done by incorporating billions of daily life devices to provide service centric facilities. With such transformation, the major traffic load will be shifted toward the backhaul networks, for which guaranteed bandwidth and low latency are the basic requirements. In order to meet varying and dynamic requirements of each service, the development of a traffic aware network is unavoidable. For achieving last mile connectivity, wireless mesh is considered among the best of the backhaul networks. Additionally, classical single radio mesh routers restrict the whole network on a single channel and hence the full potential of available multiple channels is not achieved. Mesh routers plugged with multiple radios allow parallel transmissions and increase the capacity of the whole network. To utilize network resources more efficiently, the key issue of channel assignment for wireless mesh networks is explored by incorporating the concept of time‐based traffic in a distributed environment. This paper discusses the problem of assigning a limited number of channels to a large number of radios while keeping in view the restrictions involved in maintaining a minimal level of interference and preservation of network topology. Bayesian estimation approach is used to gather knowledge from surroundings to determine the high‐interfered region and hence a distributed solution is proposed where mesh routers can find a more suitable alternative channel for respective region. The proposed algorithm is evaluated through traces on multiple flows, collected from simulations. Results show that the proposed algorithm performed better than existing ones in the presence of interference.

Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for Internet of Things (IoT). Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance (FT) in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering FT and communication delay as two conflicting objectives. An adapted nondominated sorting-based genetic algorithm (A-NSGA) is developed to solve the optimization problem. The major components of A-NSGA include chromosome representation, FT and delay computation, crossover and mutation, and nondominance-based sorting. Analytical and simulation-based comparative performance evaluation has been carried out. From the analysis of results, it is evident that the framework effectively optimizes FT for virtualization in WSNs.

With continually increased attention on electric vehicles (EVs) due to environment impact, public charging stations (CSs) for EVs will become common. However, due to the limited electricity of battery, EV drivers may experience discomfort for long charging waiting time during their journeys. This often happens when a large number of (on-the-move) EVs are planning to charge at the same CS, but it has been heavily overloaded. With this concern, in an EV charging management system, we focus on CS-selection decision making and propose a scheme to manage EVs' charging plans, to minimize drivers' trip duration through intermediate charging at CSs. The proposed scheme jointly considers EVs' anticipated charging reservations (including arrival time and expected charging time) and parking duration at CSs. Furthermore, by tackling mobility uncertainty that EVs may not reach their planned CSs on time (due to traffic jams on the road), a periodical reservation updating mechanism is designed to adjust their charging plans. Results under the Helsinki city scenario with realistic EV and CS characteristics show the advantage of our proposal, in terms of minimized drivers' trip duration, as well as charging performance at the EV and CS sides.

This paper provides an overview on side-channel attacks with emphasis on vulnerabilities in the smart home. Smart homes are enabled by the latest developments in sensors, communication technologies, internet protocols, and cloud services. The goal of a smart home is to have smart household devices collaborate without involvement of residents to deliver the variety of services needed for a higher quality of life. However, security and privacy challenges of smart homes have to be overcome in order to fully realize the smart home. Side channel attacks assume data is always leaking, and leakage of data from a smart home reveals sensitive information. This paper starts by reviewing side-channel attack categories, then it gives an overview on recent attack studies on different layers of a smart home and their malicious goals.

In Wireless Body Area Networks (WBANs), every healthcare application that is based on physical sensors is responsible for monitoring the vital signs data of patient. WBANs applications consist of heterogeneous and dynamic traffic loads. Routine patient’s observation is described as low-load traffic while an alarming situation that is unpredictable by nature is referred to as high-load traffic. This paper offers a thematic review of traffic adaptive Medium Access Control (MAC) protocols in WBANs. First, we have categorized them based on their goals, methods, and metrics of evaluation. The Zigbee standard IEEE 802.15.4 and the baseline MAC IEEE 802.15.6 are also reviewed in terms of traffic adaptive approaches. Furthermore, a comparative analysis of the protocols is made and their performances are analyzed in terms of delay, packet delivery ratio (PDR), and energy consumption. The literature shows that no review work has been done on traffic adaptive MAC protocols in WBANs. This review work, therefore, could add enhancement to traffic adaptive MAC protocols and will stimulate a better way of solving the traffic adaptivity problem.

Privacy, especially source location privacy in many Wireless Sensor Networks (WSNs) applications plays an important role in the effectiveness of these applications. Exposure of source location information in these applications may put the monitored entities or subjects in danger. Many solutions are available based on various techniques, including random walk. Most existing random walk based source location privacy preservation proposals may not work well in critical applications, because of their insufficient safety period, high energy consumption, and data delivery delay. This article proposes a novel solution for source location privacy in WSNs based on a random walk routing, especially for patient attackers to improve safety period and energy efficiency. The proposed strategy forms an Isolated Adversary Zone (IAZ) by sacrificing a certain percentage of sensor nodes and entraps patient attackers in that zone. This approach will increase safety period and energy efficiency in compared to the existing approaches as an entrapped patient attacker will wait for long time to make an attack.