Mohamad Afendee Mohamed

An Energy Aware Distributed Clustering Algorithm Using Fuzzy Logic for Wireless Sensor Networks with Non-uniform Node Distribution

AbstractClustering routing protocols are more adequate for Wireless Sensor Networks (WSNs) due to the higher energy utilization rate and scalability. However, non-uniform node deployment makes the cluster-based routing protocols less efficient, since the energy consumption of the nodes is more imbalanced. In this paper, an Energy Aware Distributed Clustering using Fuzzy Logic (EADC-FL) routing algorithm is proposed for the network with non-uniform node distribution. EADC-FL selects the most appropriate nodes as the cluster heads to save more energy in data transmission phase. It considers the energy of the sensor nodes as the primary parameter to elect the candidate cluster heads. Afterwards, it takes into consideration the node degree and node centrality of the sensor nodes by using Fuzzy Logic to identify the final cluster heads. EADC-FL constructs the clusters in equal sizes to make the energy consumption of cluster members balanced and uses a cluster-based routing algorithm to balance the energy consumption among the cluster heads. Moreover, the proposed algorithm performs clustering on demand instead of each round in order to reduce the energy dissipation of the network due to the overhead of consecutive clustering phases. The results demonstrate that EADC-FL significantly decreases the energy consumption and extends the network lifetime of network with non-uniform node distribution .

A Scheduled Activity Energy Aware Distributed Clustering Algorithm for Wireless Sensor Networks with Nonuniform Node Distribution

Nonuniform node deployment makes the cluster-based routing protocol less efficient in wireless sensor networks (WSNs). Energy aware distributed clustering (EADC) is one of the cluster-based routing protocols proposed for networks with nonuniform node distribution, which can effectively balance the energy consumption among the nodes. However, due to the nonuniform node distribution, there is a redundancy in sensed and transmitted data in dense area. This unnecessary energy consumption is not considered in EADC. Therefore, in this paper, a new algorithm called scheduled activity EADC (SA-EADC) is proposed. SA-EADC exploits the redundant nodes and turns them off for the current round. The redundant nodes are scheduled based on their residual energy to work alternatively. The results show that SA-EADC significantly decreases the energy consumption and extends the network lifetime without degradation in coverage and sensing reliability of the network.

A Review on Heuristics for Addition Chain Problem: Towards Efficient Public Key Cryptosystems

Field exponentiation and scalar multiplication are the pillars of and the most computationally expensive operations in the public key cryptosystems. Optimizing the operation is the key to the efficiency of the systems. Analogous to the optimization is solving addition chain problem. In this study, we survey from the onset of the addition chain problem to the state-of-the-art heuristics for optimizing it, with the view to identifying fundamental issues that when addressed renders the heuristics most optimal mean of minimizing the two operations in various public key cryptosystems. Thus, our emphasis is specifically on the heuristics: Their various constraints and implementations efficiencies. We present possible ways forwards toward the optimal solution for the addition chain problem that can be efficiently applied for optimal implementation of the public key cryptosystems.

Ant colony optimisation for solving university course timetabling problems

Course timetabling is one of the most important activities faced by any educational institution. Furthermore, the course timetabling process is time-consuming and tiresome as it needs to be prepared for each regular semester. This paper aims to apply the Ant Colony Optimisation (ACO) method to solve the course timetabling problem. This approach is to optimise the properties of the course requirement and minimise various conflicts for the time slot assignation. This method is based on the life of the ant colony in generating automatic timetabling according to the properties (pheromones) such as time, student, lecturer and room, besides satisfying the constraints. The implementation of this method is to find an effective and better solution for university course timetabling. The result and performance evaluation is used to determine whether it is reliable in providing the feasible timetable.

A new compression algorithm for small data communication in wireless sensor network

Energy consumption is one of the most critical issues in wireless sensor network (WSN). For a sensor device, transmission of data is considered as the most energy consuming task, and it mostly depends on the size of the data. Fortunately, data compression can be used to minimise the transmitted data size and thus extend sensors lifetime. In this paper, we propose a new lossless compression algorithm that can handle small data communication in WSNs. Using compression ratio, memory usage, number of instructions and execution speed as a comparison parameters, the proposed algorithm is measured against a set of existing algorithms. Two different datasets have been used for this purpose; namely, self-generated dataset and real sensor dataset from Harvard Sensor Library. As a result, the proposed algorithm not only outclasses other existing algorithms but most importantly produces positive compression ratio throughout the whole test where most existing algorithms experience an expansion in data size when dealing with very small data.

Incorporating the Range-Based Method into GridSim for Modeling Task and Resource Heterogeneity

Over the years, many heuristic algorithms have been proposed for solving various Grid scheduling problems. GridSim simulator has become a very popular simulation tool and has been widely used by Grid researchers to test and evaluate the performance of their proposed scheduling algorithms. As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. However, most simulation studies that based on GridSim have not considered the nature of heterogeneity. In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.

Multi-Party System Authentication for Cloud Infrastructure by Implementing QKD

In this paper, we will highlight the enhances technique to authenticate multi-party system in cloud infrastructure. We propose an enhanced tight finite key scheme for Quantum Key Distribution (QKD). With this technique we believe it can provide a secure channel between a cloud client to establish a connection between them by applying quantum theories. As a final result it shows, that it can reduce the possibility of losing a private key by producing a high efficient key rate and attack resilient. Key length is an important security measures.