Omar Banimelhem

GMCAR: Grid-based multipath with congestion avoidance routing protocol in wireless sensor networks

Recently, the interest in wireless sensor networks has been magnetized in the delay sensitive applications such as real-time applications. These time critical applications crave certain QoS requirements as though end-to-end delay guarantee and network bandwidth reservation. However, the severe resource constraints of the wireless sensor networks pose great challenges that hinder supporting these requirements. In this paper, we propose a Grid-based Multipath with Congestion Avoidance Routing protocol (GMCAR) as an efficient QoS routing protocol that is suited for grided sensor networks. We employ the idea of dividing the sensor network field into grids. Inside each grid, one of the sensor nodes is selected as a master node which is responsible for delivering the data generated by any node in that grid and for routing the data received from other master nodes in the neighbor grids. For each master node, multiple diagonal paths that connect the master node to the sink are stored as routing entries in the routing table of that node. The novelty of the proposed protocol lies behind the idea of incorporating the grids densities along with the hop count into the routing decisions. A congestion control mechanism is proposed in order to relieve the congested areas in case of congestion occurrence. Simulation results show that our proposed protocol has the potential to achieve up to 19.5% energy saving, 24.7% reduction in the delay and up to 8.5% enhancement in the network throughput when compared to another QoS routing protocol. However, when compared to the basic grid-based coordinated routing protocol, it achieves 23% energy saving. In addition, the proposed protocol shows its superiority in achieving better utilization to the available storage.

Fuzzy logic based energy efficient adaptive clustering protocol

In order to overcome the problem of the limited power of the sensor battery and thus prolonging the lifetime of a Wireless Sensor Network (WSN), many routing algorithms were proposed to gather and forward the sensed data to the base station. One of the most well-known routing algorithms that were proposed in the last years is the LEACH protocol. It is a dynamic cluster-based routing protocol that divides the network lifetime to rounds where each round is composed of two phases: setup and steady state. The key factor of each round is the number of nodes that will act as cluster heads (CHs). Each CH is responsible for collecting the sensed data from the sensor nodes that are in the same cluster and then forwarding the aggregated data to the base station. In this paper we suggest FL-LEACH protocol that employs fuzzy logic in order to determine the number of CHs that should be used in the WSN. FL-LEACH is a fuzzy inference system that depends on two variables: number of nodes in the network and nodes density. Assuming uniform distribution of the nodes over the sensor field, the novelty of the proposed approach is in its ability to determine the number of CHs without getting other information about the network. Matlab simulation is used to show the effectiveness of the FL-LEACH protocol compared with other protocols, such as the pure LEACH and the genetic-based protocol, LEACH-GA. Simulation results have shown that FL-LEACH outperforms LEACH and LEACH-GA in terms of network lifetime.

Grid-based multi-path with congestion avoidance routing (GMCAR) protocol for wireless sensor networks

A new routing protocol that handles real-time and non-real time applications in Wireless Sensor Networks (WSNs) is proposed. We employ the idea of dividing the sensor network field into grids. Inside each grid, one of the sensor nodes is selected as a master node which is responsible for delivering the data generated by any node in that grid and for routing the data received from other master nodes in the neighbor grids.

The Potential of Using Network Coding with Geographical Forwarding Routing for Wireless Multimedia Sensor Networks

In this paper, the potential of using Network Coding to enhance the performance of geographical forwarding routing for multimedia wireless sensor networks is investigated. The preliminary results of this study illustrate that Network Coding has the potential to significantly improve the average network capacity, in terms of the available number of concurrent transmission paths, which leads to several other benefits on different performance metrics such as the throughput per data flow, the end-to-end delay, and the network lifetime. The preliminary results demonstrate that, having the capability of encoding n packets at each relay node on the data path between the source nodes and the sink node can potentially improve the average network capacity by a factor bounded by n, given that the cost of performing the network coding process at each relay node, in terms of time and energy consumption, is less than that of transmitting each packet individually.

Experimental evaluation of image compression and transmission for TinyOS-based imote2 platform

In this paper, the performance of JPEG image compression and transmission using TinyOS-based Imote2 wireless sensor network platform is experimentally evaluated via a newly developed testbed. This testbed supports multihop sensor networks based on the Imote2 platform equipped with the Imote2 Multimedia Sensor Board. In addition, a standard JPEG library is embedded into the Imote2 platform to provide in-node image compression. The processing and transmission times, power consumption, and peak-signal-to-noise ratio performance metrics measurements are reported. The results show that the processing requirements are less than those of the transmission. According to the results, a tradeoff between the image quality and the energy and delay costs may be obtained.

An Energy-Balanced Cluster-Based Protocol for Wireless Sensor Networks

This paper proposes a novel energy-efficient clustering protocol for wireless sensor networks. It combines the benefits of using the k-means clustering algorithm with the, recently developed, LEACH with virtual forces LEACH-VF protocol. In this work, the k-means algorithm is employed to determine k centroids around which the clusters will be formed. After that, the virtual field force method is applied to these clusters to determine the most suitable positions for each node. The main target of such an approach is to improve the energy balance in the network and to extend the network lifetime. Simulation results show that the proposed protocol extends the time before the first node death, minimizes the variance of the average node energy, and reduces the distance that the sensor nodes travel within their respective clusters.

A Practical Study of Jointly Exploiting Multiple Image Compression Techniques for Wireless Multimedia Sensor Networks

In Wireless Multimedia Sensor Networks, the amount of multimedia traffic generated by the source nodes and relayed throughout the network towards the sink nodes is relatively vary large. As a result, the overall network performance and operational lifetime rely heavily on the efficiency and the complexity of the compression techniques used. However, known compression techniques have either high efficiency or low complexity but not both, which causes an imbalance in the distribution of the available network resources and hence shortens the network lifetime. In this work, a testbed to experimentally evaluate the performance and energy consumption of image compression and transmission was developed. Based on the testbed, the JPEG and JPEG2000 image compression algorithms were simultaneously embedded and evaluated with the purpose of jointly utilizing the features of both algorithms in order to facilitate a balanced tradeoff between the application performance requirements and the current network status. The analysis of the results verified that, in practical implementations of Wireless Multimedia Sensor Networks, using more than one compression technique by the same source node is feasible and has the potential of utilizing the capabilities of each technique based on the given situation.

Hata Path Loss Model Tuning for Cellular Networks in Irbid City

The accurate path loss models for cellular communications can help network engineers to estimate system design parameters such as base station height, antenna gain, downtilt angle, radiated power, and cell radius. Indeed, considering the appropriate path loss model in the design stage for a certain city is very important to avoid any unexpected problems after installing the system. In this paper, extensive measurements for cellular base stations are performed in Irbid city, Jordan. Based on these measurements and utilizing COST-231 Hata model, a new effective path loss model is developed and optimized using two algorithms: Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA). The new optimized model is validated by comparison with measurements for other sites. The results have shown that the optimized model using PSO and GA outperforms other models. However, the PSO algorithm performs better than GA in terms of root mean square error (RMSE) value and solution convergence speed.

A simulation testbed to jointly exploit multiple image compression techniques for wireless multimedia sensor networks

As the demand for large-scale wireless multimedia sensor networks increases, so does the need for well-designed protocols that optimize the utilization of available networks resources. This requires experimental testing for realistic performance evaluation and design tuning. However, experimental testing of large-scale wireless networks using hardware testbeds is usually very hard to perform due to the need for collecting and monitoring the performance metrics data for multiple sensor nodes all at the same time, especially the nodes energy consumption data. On the other hand, pure simulation testing may not accurately replicate the real-life scenarios, especially those parameters that are related to the wireless signal behavior in special environments. Therefore, this work attempts to close this gap between experimental and simulation testing. This paper presents a scalable simulation testbed that attempts to mimic our previously designed small-scale hardware testbed for wireless multimedia sensor networks by tuning the simulation parameters to match the real-life measurements obtained via experimental testing. The proposed simulation testbed embeds the JPEG and JPEG2000 image compression algorithms and potentially allows for network-controlled image compression and transmission decisions. The simulation results show very close match to the small-scale experimental testing as well as to the hypothetical large-scale extensions that were based on the experimental results.

A More Secure Image Hiding Scheme Using Pixel Adjustment and Genetic Algorithm

This paper proposes a more secure image hiding scheme using Optimal Pixel Adjustment Process (OPAP) and Genetic Algorithm (GA). The security issues of key selection that is used in image hiding are addressed. Thus, a more secure scheme is proposed in order to improve the security as well as the quality of the stego-image. Since GA is a semi-blind algorithm, it may select a key that affects the security. Therefore, the authores improve the security by applying image transformation not only using the GA key, but also using a user key. The user key is used to disarrange the pixel locations of the secret image. Then, the GA, using OPAP, selects the key that maximizes the quality as well as the security of the stego-image. From implementation point of view, the scheme uses a simple and fast transformation method that increases the difference between the secret image and its transformed version. The results showed that the resultant disarranged image cannot be detected, and at the same time the stego-image quality is still high.