Fast Decision Algorithms in Low-Power Embedded Processors for Quality-of-Service Based Connectivity of Mobile Sensors in Heterogeneous Wireless Sensor Networks

When a mobile wireless sensor is moving along heterogeneous wireless sensor networks, it can be under the coverage of more than one network many times. In these situations, the Vertical Handoff process can happen, where the mobile sensor decides to change its connection from a network to the best network among the available ones according to their quality of service characteristics. A fitness function is used for the handoff decision, being desirable to minimize it. This is an optimization problem which consists of the adjustment of a set of weights for the quality of service. Solving this problem efficiently is relevant to heterogeneous wireless sensor networks in many advanced applications. Numerous works can be found in the literature dealing with the vertical handoff decision, although they all suffer from the same shortfall: a non-comparable efficiency. Therefore, the aim of this work is twofold: first, to develop a fast decision algorithm that explores the entire space of possible combinations of weights, searching that one that minimizes the fitness function; and second, to design and implement a system on chip architecture based on reconfigurable hardware and embedded processors to achieve several goals necessary for competitive mobile terminals: good performance, low power consumption, low economic cost, and small area integration

An Efficient Wireless Recharging Mechanism for Achieving Perpetual Lifetime of Wireless Sensor Networks

[[abstract]]Energy recharging has received much attention in recent years. Several recharging mechanisms were proposed for achieving perpetual lifetime of a given Wireless Sensor Network (WSN). However, most of them require a mobile recharger to visit each sensor and then perform the recharging task, which increases the length of the recharging path. Another common weakness of these works is the requirement for the mobile recharger to stop at the location of each sensor. As a result, it is impossible for recharger to move with a constant speed, leading to inefficient movement. To improve the recharging efficiency, this paper takes “recharging while moving” into consideration when constructing the recharging path. We propose a Recharging Path Construction (RPC) mechanism, which enables the mobile recharger to recharge all sensors using a constant speed, aiming to minimize the length of recharging path and improve the recharging efficiency while achieving the requirement of perpetual network lifetime of a given WSN. Performance studies reveal that the proposed RPC outperforms existing proposals in terms of path length and energy utilization index, as well as visiting cycle.[[notice]]補正完

DI-SEC: Distributed Security Framework for Heterogeneous Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are deployed for monitoring in a range of critical domains (e.g., health care, military, critical infrastructure). Accordingly, these WSNs should be resilient to attacks. The current approach to defending against malicious threats is to develop and deploy a specific defense mechanism for a specific attack. However, the problem with this traditional approach to defending sensor networks is that the solution for one attack (i.e., Jamming attack) does not defend against other attacks (e.g., Sybil and Selective Forwarding). This work addresses the challenges with the traditional approach to securing sensor networks and presents a comprehensive framework, Di-Sec, that can defend against all known and forthcoming attacks. At the heart of Di-Sec lies the monitoring core (M-Core), which is an extensible and lightweight layer that gathers information and statistics relevant for creating defense modules. Along with Di-Sec, a new user-friendly domain-specific language was developed, the M-Core Control Language (MCL). Using the MCL, a user can implement new defense mechanisms without the overhead of learning the details of the underlying software architecture (i.e., TinyOS, Di-Sec). Hence, the MCL expedites the development of sensor defense mechanisms by significantly simplifying the coding process for developers. The Di-Sec framework has been implemented and tested on real sensors to evaluate its feasibility and performance. Our evaluation shows that Di-Sec is feasible on today’s resource-limited sensors and has a nominal overhead. Furthermore, we illustrate the functionality of Di-Sec by implementing four detection and defense mechanisms for attacks at various layers of the communication stack