Traditional trust management schemes developed for wired and wireless ad hoc networks are not well suited for sensor networks due to their higher consumption of resources such as memory and power. In this work, we propose a new lightweight group-based trust management scheme (GTMS) for wireless sensor networks, which employs clustering. Our approach reduces the cost of trust evaluation. Also, theoretical as well as simulation results show that our scheme demands less memory, energy, and communication overheads as compared to the current state-of-the-art trust management schemes and it is more suitable for large-scale sensor networks. Furthermore, GTMS also enables us to detect and prevent malicious, selfish, and faulty nodes.

Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks.

Wireless sensor networks (WSNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient network. In this paper, we propose an energy aware geographical multipath routing scheme for WSNs. The distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection, and Analytical Hierarchy Process (AHP) is applied for decision making. Simulation results show that this scheme can extend the network lifetime longer than the original geographical routing scheme which only considers distance to the destination location. Moreover, the proposed scheme can reduce the packet loss rate and link failure rate since the buffer capacity is considered.

The linear array with a reconfigurable pipelined bus system (LARPBS) is an optical bus-based theoretical parallel computation model. Many parallel algorithms have been proposed using this model of computation. However, a current limitation of the LARPBS model is that it does not provide for performance prediction of these algorithms running on realistic implementations of the LARPBS model. This paper investigates the parameterization of the LARPBS model so as to overcome this limitation. Specifically, a new parameterized parallel computation model, the LARPBS(p) model, is proposed in this paper. The LARPBS(p) model captures computational costs through six abstract parameters: the number of processors, the communication latency, the communication overhead, the network capacity, the computation time and the synchronization time. The proposed parameters and, subsequently, the cost analysis on the LARPBS(p) model are presented. In addition applications of the cost analysis to some primitive operations and to two matrix multiplication algorithms on the LARPBS(p) are also presented. LARPBS(p) is intended to serve as a basis for a more accurate estimation of execution time of algorithms by providing greater detail of the costs involved on the LARPBS.