Ahmed Salim

IBLEACH: intra-balanced LEACH protocol for wireless sensor networks

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Recent advances in wireless networks have led to many new protocols specifically designed for WSNs where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Minimizing energy dissipation and maximizing network lifetime are important issues in the design of routing protocols for WSNs. In this paper, the low-energy adaptive clustering hierarchy (LEACH) routing protocol is considered and improved. We propose a clustering routing protocol named intra-balanced LEACH (IBLEACH), which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that IBLEACH outperforms LEACH and the existing improvements of LEACH in terms of network lifetime and energy consumption minimization.

Distributed multi chain compressive sensing based routing algorithm for wireless sensor networks

In wireless sensor networking applications, collecting sensed data and relaying it to the base station in an energy efficient manner is of paramount importance. It follows that power management and energy-efficient communication techniques become necessary to maximize network lifetime for wireless sensor networks (WSNs). In this paper, our objective is to distribute energy consumption evenly and maximize the network lifetime by utilizing data aggregation and in-network compression technique. We mainly focus on the combined problem of data routing with data aggregation during routing such that minimizing the number of packets to transmit and achieve our objective. We propose a multi chain routing algorithm executed with compressive sensing for data aggregating in WSNs. We show that by using our compressive sensing based routing algorithm significant reduction in data traffic can be achieved, resulting in power saving and thus prolong the network lifetime.

Decomposable algorithms for nearest neighbor computing

Privacy and security concerns can prevent sharing of data, derailing many data projects. Distributed knowledge computing, if done correctly, can alleviate this problem. The key is to obtain valid results, while providing guarantees on the (non)disclosure of data. In the present study, two novel algorithms have been developed to find the nearest neighbor from known points, and a pair of nearest neighbors in a given set data points in d-dimensional space in distributed databases. These algorithms preserve the privacy and security of the data at individual sites by requiring transmission of only minimal information to other sites.

Sparse Signals Reconstruction via Adaptive Iterative Greedy Algorithm

Compressive sensing(CS) is an emerging research field that has applications in signal processing, error correction, medical imaging, seismology, and many more other areas. CS promises to efficiently reconstruct a sparse signal vector via a much smaller number of linear measurements than its dimension. In order to improve CS reconstruction performance, this paper present a novel reconstruction greedy algorithm called the Enhanced Orthogonal Matching Pursuit (E-OMP). E-OMP falls into the general category of Two Stage Thresholding(TST)-type algorithms where it consists of consecutive forward and backward stages. During the forward stage, E-OMP depends on solving the least square problem to select columns from the measurement matrix. Furthermore, E-OMP uses a simple backtracking step to detect the previous chosen columns accuracy and then remove the false columns at each time. From simulations it is observed that E-OMP improve the reconstruction performance better than Orthogonal Matching Pursuit (OMP) and Regularized OMP (ROMP).

Distributed coverage hole detection and recovery scheme for heterogeneous wireless sensor networks

Abstract In Wireless sensor networks (WSNs), the coverage problem is a fundamental issue. The coverage holes are generally caused by both, random deployment of the sensor nodes and node failures, and are hardly avoided in WSNs. It is impossible to recharge or replace the battery, and therefore, the collaborative detection and prediction of coverage holes and recovery of these holes has strategic importance in WSNs specially in heterogeneous WSNs (HWSNs). In this paper, a new scheme is proposed which includes distributed algorithms for detecting holes caused by both random deployment and node failures in HWSNs, where nodes can collaborate to detect and predict the coverage holes. This scheme also presents the new coverage holes healing algorithm, which can efficiently leverage mobility to optimize the average coverage rate and the average movement distance of the mobile nodes. The performance results of our scheme exceeds the existing algorithms in terms of coverage and energy saving.

Effect of using Mobile Sink on Chain-based Routing Protocols in Wireless Sensor Networks

In this paper, we examine some protocols related to WSNs. To evaluate the efficiency of different routing schemes, we compare six chain based routing protocols; Power Efficient Gathering in Sensor Information Systems (PEGASIS), Power Efficient Gathering in Sensor Information System Extended (PEGASIS-E), Chain Oriented SEnsor Network (COSEN), Energy Efficient Chain Based Sensor Network (ECBSN), Improved Energy Efficient Chain Based Sensor Network (IECBSN), and Energy-Aware PEGASIS-Based Hierarchal Routing Protocol for Wireless Sensor Networks (EAPHRN). Two scenarios are discussed to compare the performances of chain based routing protocols; in the first scenario static sink is used and in the second one mobile sink is used. We perform analytical simulations in terms of network lifetime and average energy consumption.