Abas Md Said

A survey of simulators, emulators and testbeds for wireless sensor networks

Simulators, emulators and testbeds are invaluable tools for performance evaluation of algorithms and protocols in wireless sensor networks (WSNs). It is extremely difficult to choose an appropriate tool for performance testing without the horizontal and vertical analysis of existing tools. This paper presents a survey of thirty five performance evaluation tools for WSNs. Unlike most other studies, tools were selected based on their popularity, support for WSNs, active maintenance and the help available. On the horizontal dimension, prominent competitors at each stage were selected. For vertical analysis, tools for simulation, emulation and testbeds were categorized accordingly. We believe that this survey will aid researchers, application and tool developers while selecting an appropriate tool for their implementation. We have highlighted an open research issue to have an integrated tool that supports modeling, simulation, emulation and testbed implementation for algorithm validation, performance evaluation and proof-of-concept implementation in WSNs.

Localized motion-based connectivity restoration algorithms for wireless sensor and actor networks

In wireless sensor and actor networks maintaining inter-actor connectivity is very important in mission-critical applications where actors have to quickly plan optimal coordinated response to detected events. Failure of one or multiple actors may partition the inter-actor network into disjoint segments, and thus hinders the network operation. Autonomous detection and rapid recovery procedures are highly desirable in such a case. This paper presents DCR, a novel distributed partitioning detection and connectivity restoration algorithm to tolerate the failure of actors. DCR proactively identifies actors that are critical to the network connectivity based on local topological information, and designates appropriate, preferably non-critical, backup nodes. Upon failure detection, the backup actor initiates a recovery process that may involve coordinated relocation of multiple actors. We also present an extended version of DCR, named RAM, to handle one possible case of a multi-actor failure. The proposed algorithms strive to avoid procrastination, localize the scope of recovery and minimize the movement overhead. Simulation results validate the performance of the proposed algorithms.

Volunteer-instigated connectivity restoration algorithm for Wireless Sensor and Actor Networks

Due to their applications, Wireless Sensor and Actor Networks (WSANs) have recently been getting significant attention from the research community. In these networks, maintaining inter-actor connectivity is of a paramount concern in order to plan an optimal coordinated response to a detected event. Failure of an actor may partition the inter-actor network into disjoint segments, and may thus hinder inter-actor coordination. This paper presents VCR, a novel distributed algorithm that opts to repair severed connectivity while imposing minimal overhead on the nodes. In VCR the neighbors of the failed actor volunteer to restore connectivity by exploiting their partially utilized transmission range and by repositioning closer to the failed actor. Furthermore, a diffusion force is applied among the relocating actors based on transmission range in order to reduce potential of interference, and improve connectivity. VCR is validated through simulation and is shown to outperform contemporary schemes found in the literature.

Partitioning Detection and Connectivity Restoration Algorithm for Wireless Sensor and Actor Networks

Recently, Wireless Sensor and Actor Networks have been receiving a growing attention from the research community because of their suitability for critical applications. Maintaining inter-actor connectivity becomes extremely crucial in such situations where actors have to quickly plan optimal coordinated response to detected events. Failure of critical actor partitions the inter-actor network into disjoint segments, and thus hinders the network operation. Autonomous detection and rapid recovery procedures are highly desirable in such case. This paper presents PCR, a novel distributed partitioning detection and connectivity restoration algorithm. PCR proactively identifies critical actors based on local topological information and designate appropriate backup nodes (preferably non-critical) to handle their failure. A backup actor detects the failure and initiates a recovery process that may involve coordinated multi-actor relocation. The purpose is to avoid procrastination, localize the scope of recovery process and minimize the movement overhead. Simulation results validate the performance of PCR that outperforms contemporary schemes found in literature.

Internet Call Delay on Peer to Peer and Phone to Phone VoIP Network

VoIP (Voice over Internet Protocol) is a technology that enables the routing of voice conversations over any IPbased network such as the public Internet. Separate and distinct client, gateway and call control functions that ability to support Peer-to-Peer, PC-to-telephone, telephone-to-PC and telephone-to-telephone scenarios. During transmission, the traffic loading and other factors in the IP (Internet Protocol) network may cause packets to be lost. Three parameters emerge as the primary factors affecting voice quality within networks that offer VoIP technologies: clarity, end-to-end delay and echo delayed. The objective of this research is to check internet call delay over VoIP on Peer-to-Peer and telephone-to-telephone communication. The methodology used Sources of echo for test different type of call over VoIP. We used IPv4 (Internet Protocol Version 4), CISCO 3700 Series Router and telephone sets for experimentation. We checked QoS (Quality of Service) development on various sample signals. The tests were used templates varied in loudness,speech continuity, background noise and delay. We analyzed both male and female voices for results.

Application-centric connectivity restoration algorithm for wireless sensor and actor networks

This paper presents ACR, a novel hybrid application-centric connectivity restoration algorithm that factors in application level interests besides efficient resource utilization while recovering from critical node failures. As a pre-failure planning measure to minimize recovery delay, ACR identifies primary actors that are critical for network connectivity based on localized information and designates them for backup nodes. The backup nodes are carefully picked to satisfy application level concerns such as high actor effectiveness. In order to minimize the impact of critical node failure on coverage and connectivity, ACR appoint high degree nodes with overlapped coverage. Upon failure detection, the pre-designated backup pursues controlled and coordinated movement to replace the failed node. Simulation results validate the performance of ACR.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth.

Enhanced performance of packet transmission using system model over VoIP network

Transmission of multimedia data in Voice over Internet Protocol (VoIP) network is challenging. Packet loss, delay, jitter, etc. highly degrade the performance of the network. Hence more robust techniques are required to provide better level of service quality. One crucial parameter to measure service quality is packet loss. The objective of this paper is to analyze the impact of packet loss and identify proper codec techniques for VoIP traffic. We used a packet analyzer tool (wireshark) to analyze the voice traffic. We found that wireshark could serve as an effective tool for packet loss analysis. It helped us in identifying the proper codec technique that should be used for an enhanced performance in a VoIP network.

Decreasing packet loss for QoS sensitive IP traffic in DiffServ enabled network using MPLS TE

More telecommunication services are using Internet as single network for voice, video and data transmission. Quality of Service (QoS) guarantee is necessary for such transmission over the internet backbone. Internet is not a simple best-effort network only for web traffic anymore. It is generally understood that present internet best-effort infrastructure is not sufficient to provide QoS-guaranteed services. DiffServ is developed to classify internet traffic into different classes, where each class has predefined QoS parameters. DiffServ can be deployed to ensure QoS, but it is unable to deliver QoS guarantees for the network as whole. Using Multi Protocol Label Switching Traffic Engineer (MPLS TE) we have a dynamic overview of network resources and so we can route the traffic in the whole network satisfying QoS needs for each traffic class, like voice, video, real time etc. In this paper we have demonstrated the usefulness of applying Differenciated Services (DiffServ) and MPLS TE in the network to reduce packet drops for drop sensitive applications keeping the network resources utilization optimized. After application of MPLS TE in a DiffServ enabled network IP backbone we have significantly reduced packet loss.

Data Mining of Protein Sequences with Amino Acid Position-Based Feature Encoding Technique

Biological data mining has been emerging as a new area of research by incorporating artificial intelligence and biology techniques for automatic analysis of biological sequence data. The size of the biological data collected under the Human Genome Project is growing exponentially. The available data is comprised of DNA, RNA and protein sequences. Automatic classification of protein sequences into different groups might be utilized to infer the structure, function and evolutionary information of an unknown protein sequence. The accurate classification of protein sequences into family/superfamily based on the primary sequence is a very complex and open problem. In this paper, an amino acid position-based feature encoding technique is proposed to represent a protein sequence using a fixed length numeric feature vector. The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 % classification accuracy over the Yeast protein sequence dataset.