Wireless sensor networks have been the subject of intense research in recent years. Sensor nodes are used in wide range of applications such as security, military, and environmental monitoring. One of the most interesting applications in wireless sensor networks is target tracking, which mainly consists in detecting and monitoring the motion of mobile targets. In this paper, we present a comprehensive survey of target tracking approaches. We then analyze them according to several metrics. We also discuss some of the challenges that influence the performance of tracking schemes. In the end, we conduct detailed analysis and comparison between these algorithms and we conclude with some future directions.

Abstract:Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers' computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

<p class="0abstract"><span lang="EN-US">The Constrained Application Protocol (CoAP) is one of the most emerging messaging protocols that have successfully fulfilled the need of the lightweight feature required to handle communication between constrained devices in IoT environment. However, these devices are generating a huge amount of messages and notifications which cause the network congestion. Then, the challenge addressed in this paper; consists of designing a suitable congestion control mechanism for CoAP that ensures a safe network operation while keeping the use of network resources efficient. To do so, this paper presents an improved congestion control algorithm for the estimation of a Retransmission Time Out (RTO) value to use in each transaction based on the packet loss ratio and the Round-Trip Time RTT of the previous transmission. A comprehensive analysis and evaluation of simulated results show that the proposed mechanism can appropriately achieve higher performance compared to the basic CoAP congestion control and alternative algorithms based on TCP.</span></p>

Purpose -Energy consumption has always been the most serious issue to consider while deploying wireless sensor networks (WSNs). Sensor nodes are limited in power, computational capacities and memory so reporting the occurrence of specific events, such as fire or flooding, as quickly as possible using minimal energy resources is definitely a challenging issue. The purpose of this paper is to propose a new, reactive and energy-efficient scheme for reporting events. In this scheme, nodes that detect a certain event will organize themselves into a cluster, elect a clusterhead that will collect data from the cluster members, aggregate it and forward it to the mobile sink. Design/methodology/approach -In order to evaluate the scheme, a new sensor node model was designed, where the network layer is implemented from scratch. This layer contains the state process model of the algorithm which was made available through a high-fidelity process modeling methodology. Findings -Simulation results show that a high-event notification delivery ratio and a significant energy saving is achieved by deploying the proposed sensor node model; comparisons with existing methods show the efficiency of using the new scheme. Originality/value -The new contribution in this paper is a novel, reactive and energy-efficient scheme for reporting events over WSNs. The concept introduced in this paper will decrease energy consumption inside the network and, thus, improve its lifetime.