Lutful Karim

Wireless Sensor Network-based air quality monitoring system

This paper proposes a simple Wireless Sensor Network (WSN)-based air quality monitoring system (WSN-AQMS) for industrial and urban areas. The proposed framework comprises a set of gas sensors (ozone, CO, and NO2) that are deployed on stacks and infrastructure of a Zigbee WSN and a central server to support both short-term real-time incident management and a long-term strategic planning. This architecture would use open-hardware open-software gas sensing capable motes [6] made by Libelium. These motes use the ZigBee communication protocol and provide a real-time low cost monitoring system through the use of low cost, low data rate, and low power wireless communication technology. The proposed monitoring system can be transferred to or shared by other applications. We also introduce a simple but efficient clustering protocol dubbed hereafter “Clustering Protocol for Air Sensor network” (CPAS) for the proposed WSN-AQMS framework. CPAS proves to be efficient in terms of network energy consumption, network lifetime, and the rate at which data is communicated.

Localization in terrestrial and underwater sensor-based m2m communication networks: architecture,classification and challenges

Summary n nLocalizing machine-type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine-to-machine (M2M) communication networks for location-based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor-based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading-off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state-of-the-art research on both terrestrial and underwater localization approaches for sensor-based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them. Copyright

Range-free localization approach for M2M communication system using mobile anchor nodes

Most existing range-free localization approaches use static anchor nodes. These approaches cannot be used for large scale Machine to Machine (M2M) communication networks since a fixed number of static anchor nodes cannot localize Machine Type Communication (MTC) devices such as sensors whenever more MTC devices are deployed in the network. Thus, this article introduces a Range-free, Energy efficient, Localization technique that uses Mobile Anchor (RELMA) nodes. This approach is scalable since the anchor nodes can move close to the newly deployed MTC devices in the network to localize them. The un-localized MTC devices receive beacon messages with the location information of mobile anchors whenever the anchors are within the sensing range of un-localized devices. Thus, RELMA is energy efficient and accurate because (i) the sensing range is much shorter than the communication range that other approaches use, and (ii) the intersected region of three sensing circles, where the un-localized device resides in, is very small. Simulation results show that RELMA outperforms existing Neighbor information Based Localization Scheme (NBLS) and Sink at the Origin Localization (SOL) approaches in terms of localization error and network energy consumption.

Fault tolerant, energy efficient and secure clustering scheme for mobile machine-to-machine communications

Designing energy efficient, fault tolerant and secure clustering scheme is important for machine-to-machine M2M communications that comprise a large number of sensors. Existing works on M2M communications include designing M2M layered architecture, device model, Quality of Service QoS categorisation of M2M services and potential M2M applications. However, designing secure and fault tolerant clustering schemes has not received much attention in M2M research. Thus, this paper introduces a fault tolerant, energy efficient and secure clustering scheme for M2M FESM area networks that minimises the number of cluster heads CHs and active nodes to reduce network energy consumption. The machine type communication gateway and CHs transmit beacon messages to discover the failure of CHs and member nodes, respectively. The security mechanism is lightweight but efficient. It uses simple permutation-based shared keys between i member nodes and CHs; ii gateway nodes and CHs; and iii CHs and machine type communication gateway. Experimental results demonstrate that the FESM clustering scheme reduces network energy consumption and increases network lifetime as compared with the existing Fault Tolerant and Energy Efficient Clustering Protocol FTEEC, Dynamic Static Clustering Protocol DSC and Low Energy Adaptive Clustering Hierarchy LEACH protocols. We also analyse the security mechanism of the FESM protocol and find that it is very effective against well-known attacks such as sybil, wormhole and black hole. Copyright

An energy efficient, fault tolerant and secure clustering scheme for M2M communication networks

Machine to Machine (M2M) communication networks starts to achieve widespread usability in different application domains. Thus, designing energy efficient, fault tolerant and secure clustering scheme is significantly important for the M2M area networks that comprise a large number of sensors. However, to the best of our knowledge, existing secure clustering schemes for M2M communication networks do not support fault tolerance and energy efficiency together. Thus, this paper introduces an Energy efficient, fault tolerant and Secure clustering mechanism for M2M (ESM) area networks that minimizes the number of cluster heads (CHs) and active member nodes. The ESM clustering scheme includes a simple, lightweight but very effective security mechanism that uses simple permutation-based shared keys between (i) member nodes and CHs, (ii) inter-cluster gateway nodes and CHs and (iii) CHs and Machine Type Communication (MTC) gateway. Experimental results demonstrate that the ESM clustering scheme reduces network energy consumption as compared to the existing DSC and LEACH protocols. Security analysis also reveals that ESM is effective against well-known attacks such as sybil, wormhole, and black hole.

Heterogeneous mobility and connectivity-based clustering protocol for wireless sensor networks

Wireless sensor networks (WSNs) have received significant research focus due to their widespread applicability in military, health care, agriculture, environment monitoring applications. These applications require WSNs to be self-organized and mobile. Clustering techniques are particularly important in the success of WSN implementations especially when sensor nodes are moving at different speeds. Many existing clustering algorithms assume that sensor nodes move at the same speed which is not true in many practical cases. Thus, in this paper, we introduce a velocity-based clustering algorithm and implement a relay placement technique in order to maintain seamless network connectivity. Simulation results show that the packet loss rate of the proposed algorithm is much lower than the existing LEACH and HEED clustering protocols.

Distributed Gateway Selection for M2M Communication in Cognitive 5G Networks

M2M communication is an important component for future wireless networks. M2M systems consist of a large number of devices that can operate with minimum or no human intervention. However, spectrum demand rises exponentially with the increase in the number of connected devices. Cognitive 5G networks are key to address the issue of spectrum scarcity. Further, use of multiple gateways in cognitive 5G networks for M2M communication can increase system throughput, coverage, and energy efficiency. Nevertheless, using multiple gateways for the secondary M2M devices may cause interference to the primary M2M devices. Existing gateway selection protocols for cognitive M2M communication mostly use single channel CSMA, and thus are not efficient in terms of reducing the interference. Thus, in this article, we propose a DGAP based on multi-channel CSMA for M2M communication in 5G networks. Further, we propose a Lo-DGAP, where each gateway transmits only the worst primary M2M device information rather than transmitting all neighboring primary M2M device information. The proposed Lo-DGAP increases the throughput of the system by reducing the message header payload and is also energy- efficient. Simulation results demonstrate the effectiveness of the proposed schemes in terms of network lifetime and energy consumption.

Reliability model for multimedia cloud networks: poster

Multimedia cloud data center is the core component of the multimedia cloud networks. In the cloud data center, software, service and storage visualizations are realized through the deployment of virtual machines (VMs). The reliability of multimedia service depends on the reliability of the data center as well as the reliability of the deployment and redundancy model of VMs. In this poster, we consider four deployment scenarios for VMs such as parallel, triple modular, triple modular/simplex, K-out-N redundancy model from the reliability point of view. The reliability performance using these redundancy models is presented and compared in this poster.

Computationally Efficient, Dynamic distributed Algorithm of sensor-based Big Data

With the emergence of big data, designing an efficient distributed algorithm is significantly important. While most existing distributed algorithms consider distributed processing only for commodity computers, this paper introduces a Computationally Efficient, Dynamic distributed Algorithm (CEDA) for big data processing on a framework that comprises data processing both at the data collection end and data processing at the central server end. The proposed CEDA algorithm works both in low powered nodes and high speed commodity computers. Additionally, it performs sequential and parallel processing based on the amount of data received at the central server. Simulation results demonstrate that the CEDA algorithm achieves processing efficiency in terms of data processing time as compared to traditional distributed algorithms, which do not consider processing data at sensors.

Efficient connectivity preserving clustering protocol for mobile sensor network

Ensuring connectivity among mobile nodes is significantly important to the success of many critical applications, like military, where the loss of connectivity can lead to the failure of the mission and also proved to be challenging in particular when mobiles nodes have heterogeneous mobility pattern i.e., they are moving in several directions at different speeds. In this paper, we propose a new Heterogonous Mobility Pattern Clustering (HMPC) algorithm in which spatial and temporal densities are used. In our approach, we implement Density Based Spatial Clustering Application Noise (DBSCAN) in which the temporal aspect of a Minimum Period of Connectivity (MPC) is taken into consideration. Border nodes are used to reestablish connectivity among disconnected sub-clusters by increasing the communication range of the best suitable border nodes. Using three different mobility scenarios, simulation results show that the proposed HMPC outperforms two other typical clustering algorithms LEACH and HEED in term of connectivity as it provides better packets delivery ratio and smaller packets loss ratio.