Showing papers by "Sabah M. Ahmed published in 2016"

An Unequal Multi-hop Balanced Immune Clustering protocol for wireless sensor networks

Abstract: Display Omitted An Unequal Multi-hop Balanced Immune Clustering protocol (UMBIC) is proposed.UMBIC solves the hot spot problem and improves the lifetime of networks.UMBIC adjusts the intra-cluster and inter-cluster energy dissipation of clusters.UMBIC utilizes the multi-objective immune algorithm to finds the optimum clusters.Simulation experiments were conducted in MATLAB correctly. In multi-hop routing, cluster heads near the base station act as relays for far cluster heads and thus will deplete their energy very quickly. Thus, hot spots in the sensor field result. This paper introduces a new clustering algorithm named an Unequal Multi-hop Balanced Immune Clustering protocol (UMBIC) to solve the hot spot problem and improve the lifetime of small and large scale/homogeneous and heterogeneous wireless sensor networks with different densities. UMBIC protocol utilizes the Unequal Clustering Mechanism (UCM) and the Multi-Objective Immune Algorithm (MOIA) to adjust the intra-cluster and inter-cluster energy consumption. The UCM is used to partition the network into clusters of unequal size based on distance with reference to base station and residual energy. While the MOIA constructs an optimum clusters and a routing tree among them based on covering the entire sensor field, ensuring the connectivity among nodes and minimizing the communication cost of all nodes. The UMBIC protocol rotates the role of cluster heads among the nodes only if the residual energy of one of the current cluster heads less than the energy threshold, as a result the time computational and overheads are saved. Simulation results show that, compared with other protocols, the UMBIC protocol can effectively improve the network lifetime, solve the hot spot problem and balance the energy consumption among all nodes in the network. Moreover, it has less overheads and computational complexity.

A comparative approach between cepstral features for human authentication using heart sounds

Abstract: The main objective of this paper is to provide a comparative study between different cepstral features for the application of human recognition using heart sounds. In the past 10 years, heart sound, which is known as phonocardiogram, has been adopted for human biometric authentication tasks. Most of the previously proposed systems have adopted mel-frequency and linear frequency cepstral coefficients as features for heart sounds. In this paper, two more cepstral features are proposed. The first one is based on wavelet packet decomposition where a new filter bank structure is designed to select the appropriate bases for extracting discriminant features from heart sounds. The other is based on nonlinear modification for mel-scaled cepstral features. The four cepstral features are tested and compared on two databases: One consists of 21 subjects, and the other consists of 206 subjects. Based on the achieved results over the two databases, the two proposed cepstral features achieved higher correct recognition rates and lower error rates in identification and verification modes, respectively.

Heart-ID: human identity recognition using heart sounds based on modifying mel-frequency cepstral features

Abstract: This study presents a new framework for human identity recognition using heart sound signals. The proposed framework is based on extracting cepstral features from heart sound signals, which are known as phono-cardio-gram (PCG). Two well-known cepstral features have been adopted in most of the previously implemented PCG biometric authentication systems; namely, mel-frequency and linear frequency cepstral features. In this study, two more cepstral features are proposed based on modifying the mel-frequency cepstral features. The first one is based on modifying the mel-frequency equation to increase the non-linearity of the triangular filters in the frequency range of the PCG signal. The other is based on replacing mel-scaled triangular filters with wavelet packet filters where a non-linear filter bank structure is designed using wavelet packet decomposition to select the appropriate bases for extracting discriminant features. The proposed system uses wavelet de-noising for pre-processing and linear discriminant analysis for classification. The proposed system is evaluated on two databases; one consists of 21 users (BioSec. database) and the other consists of 206 users (HSCT-11 database). Moreover, the proposed system is compared with previous systems that used the same databases. On the basis of the achieved results over the two databases, the two proposed cepstral features achieved higher correct recognition rates and lower error rates in identification and verification modes, respectively.

An Immune-Based Energy-Efficient Hierarchical Routing Protocol for Wireless Sensor Networks

Abstract: The energy-efficiency is the primary design issue, which greatly affects the lifetime of Wireless Sensor Network (WSNs). The hierarchical-based routing is a feasible solution for reducing the energy consumption in WSNs due to reduction of the redundant data transmission. In the hierarchical routing, the network is partitioned into clusters, where each cluster consists of a head node and many member nodes. Selection of the best head nodes, that improve the lifetime and the performance of WSNs, is a NP-hard problem. Thus, this paper proposes an Immune-based Energy-Efficient hierarchical Routing Protocol (IEERP) to improve the lifetime of WSNs. IEERP utilizes the Multi-Objective Immune Algorithm (MOIA) to partition the network into optimum clusters and find locations of the best cluster heads on the basis of balancing the consumption energy among the sensor nodes and minimizing the dissipated energy in communication and overhead control packets. The operation of the proposed IEERP protocol is divided into rounds, where each round consists of two phases. The first phase is the cluster building phase, in which sink uses the MOIA algorithm to find locations of the optimum cluster heads, followed by the data transmission phase, in which the sensor nodes transfer their sensed data to the sink via the determined cluster heads. Simulation results cleared that the IEERP is more reliable protocol because it improvers the stability period and the lifetime of the homogeneous and the heterogeneous WSNs as compared to the other protocols.