International Journal of Advanced Networking and Applications

Hamdy H. El-Sayed ¹, Hassan Shaban Hassan ²

Affiliations
1 Sohag University, EG
2 Minia University, EG

Abstract

Wireless Sensor Networks (WSN) is composed of small sensor nodes which may be hundreds or multi hundreds or thousands in number. Sensor nodes, also known as mote, are small, lightweight and portable devices equipped with a transducer, microcomputer, transceiver, and power source. Based on the network topology, routing protocols in sensor networks can be classified as flat-based routing, hierarchical-based routingand location-based routing. This paper studied some hierarchical-based routing protocols and evaluated these protocols with different cluster head probability in medium network with 200 nodes number. Protocols like Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy-Efficient Clustering (DEEC), Threshold sensitive Energy Efficient sensor Network protocol (TEEN) and Stable Election Protocol (SEP) are used for our comparisons. We evaluate the performance of these protocols for a cluster head probability sensing application. Cluster head Probability effects on throughput, overhead, packet delivery ratio, alive nodes and dead nodes, as parameters used to measure the performance of these protocols. We observed new results and different comparisons for hierarchical protocols in WSN.

Keywords

Alive Nodes, Dead Nodes, Packet Delivery Ratio, Throughput.

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Hamdy H. El-Sayed ¹

Affiliations
1 Sohag University, EG

Abstract

Wireless sensor network (WSN) consists of small devices, which are called sensors.It is capable of sensing the environmental events, make processing of them and send data to the base station (BS), which needs high energy for its usage. This network which is limited to iterate the dead nodes, bring by energydepletion and to maximize the life-span of the system. Many routing protocols have been proposed and the efficiency of WSN declines as changing of the parameters of sensor nodes. The protocols in WSN are classified to heterogeneous or homogeneous. In this paper, we test the effects of node density and network area on various distributed energy- efficient clustering based on protocols such as Distributed Energy-Efficient Clustering (DEEC), Developed Distributed Energy-Efficient Clustering (DDEEC) and Threshold Distributed Energy-Efficient Clustering (TDEEC) as multilevel heterogeneous protocols, and MODLEACH protocols as an example of homogeneous routing protocols. Threshold Distributed Energy-Efficient Clustering protocol has better performance than Distributed Energy-Efficient Clustering protocol, Distributed Energy-Efficient Clustering protocol and Enhanced Distributed Energy-Efficient Clustering protocol (EDEEC) but Modified Low Energy Adaptive Clustering Hierarchy protocol (MODLEACH) is lengthy the stable period other than protocols. The sent packet to BS and the received one from BS are increased with increasing of nodes number and decreased with increasing of network area. The life time of network decreases conversely with increasingthe area of transmission. These parameters will increase the performance of the entire network. Especially in real-time applications that use the WSNs, which, are expected to work in fields such as industry, rubout or battle tracking.

Keywords

Energy-Efficient Clustering Protocol, Wireless Sensor Networks, Heterogeneous and homogeneous protocols, Distributed algorithms, Network performances.

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Hamdy H. El-Sayed ¹, E. A. Zanaty ¹, Samy S. Bakeet ¹, Elham M. Abd-Elgaber ¹

Affiliations
1 Faculty of Computers and Artificial Intelligence, Sohag University, Sohag, EG

Abstract

In recent years, researchers have focused on wireless sensor networks (WSNs). Because there are a lot of applicationswe used. The wireless sensor network consists of many small sensor nodes that contain a small and self-charged battery. Sometimes it is possible to change the power source of the node battery but sometimes it is impossible to do so, and this varies depending on the nature of the network environment so, the wireless sensor network may be destroyed over time. This makes the process of increasing the lifetime of the wireless sensor network a major challenge for researchers. There are a lot of WSN protocols to improve the lifetime of WSN, one of these protocols and some of its modified versions.

In this paper, LEACH is used to investigatewireless sensor networks (WSN) byevaluating LEACH, LEACH-C, LEACH-B (balanced leech), MOD-LEACH, I-LEACH, and Multi-hop LEACH. Moreover, The LEACH, LEACH-C, LEACH-B (balanced leech), MOD-LEACH, I-LEACH, and Multi-hop LEACH are implemented by MATLAB to achieve simulation results. The performance evaluation is shown in more charts to prove the performance of these protocols.

Keywords

ModifiedLEACH Protocols, Alive Nodes, Packet to BS, Packet to CH, Energy of Network, WSN.

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Hamdy H. El-Sayed ¹, Zainab Mostafa Hashem ²

Affiliations
1 Faculty of Computers and Artificial Intelligence, Department of Computer Science, Sohag University, Sohag, 82524, EG
2 Faculty of Science, Department of Computer Science, Sohag University, Sohag, 82524, EG

Abstract

The main thing we work on is Wireless Sensor Networks (WSNs) which contain numerous sensor nodes with limited power resources, which report sensed data to the Base Station (BS) that requires high energy usage. We want to let the battery live as long as we can, as the cost of changing batteries of nodes is high and also difficult. So, we use efficient protocols which improve the way the sensors use to send and receive sensed data to BS on other hand, nodes closer to the base station are exploited as they have to spend additional energy in relying on data of faraway nodes. This brings in the idea of implementing blanket coverage in heterogeneous wireless sensor networks for the internet of things. In this paper, we first test Distributed Energy Efficient Clustering (DEEC), Developed DEEC (DDEEC), Enhanced DEEC (EDEEC), Threshold DEEC (TDEEC), and Improved DEEC Protocol (IDEEC) under several different scenarios. We observe thoroughly the performance based on stability period, network lifetime, and throughput. EDEEC and TDEEC perform better in all heterogeneous scenarios containing variable heterogeneity in terms of lifetime, however, TDEEC is best of all for the stability period of the network. IDEEC is better than DDEEC in terms of Overhead, but TDEEC is the best. However, the performance of DEEC and DDEEC is highly affected by changing the heterogeneity parameters of the network.

Keywords

Cluster, Head, Residual, Energy, Efficient, Wireless, Sensor, Networks , Heterogeneous network, Stability period, Initial energy, IoT, DEEC, DDEEC, EDEEC, IDEEC,TDEEC.

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Hamdy H. El-Sayed ¹

Affiliations
1 Faculty of Computers and Artificial Intelligence, Sohag University, Egypt., EG

Abstract

This paper study the efficient use of energy as a challenging task of designing these protocols. The energy holes are created due to non-uniform node distribution in the network when quickly drain the energy in a few nodes. It is studies removing energy holes by using sleep and awake mechanism for sensor nodes to save energy. This approach finds the maximum distance nodes to calculate the maximum energy for data. It intends to enumerate the dead nodes transmission, alive nodes, throughput, overhead and packet delivery ratio consumed by the entire network and affected by the network area changes. lastly, a brief performance analysis of Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy-Efficient Clustering (DEEC), Threshold sensitive Energy Efficient sensor Network protocol (TEEN) and Stable Election Protocol (SEP) is carried out considering metrics of the previous characteristics of wireless sensor network.

Keywords

Dead Nodes, Alive Nodes, Throughput, Overhead, Packet Delivery Ratio, Protocols, WSN.

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Ahmed Y. Hamed ¹, M. Kh. Elnahary ¹, Hamdy H. El-Sayed ¹

Affiliations
1 Faculty of Computers and Artificial Intelligence, Department of Computer Science, Sohag University, Sohag, 82524, EG

Abstract

Cloud computing is now dominant in high-performance distributed computing, offering resource polling and on-demand services over the web. So, the task scheduling problem in a cloud computing environment becomes a significant analysis space due to the dynamic demand for user services. The primary goal of scheduling tasks is to allocate tasks to processors to achieve the shortest possible makespan while respecting priority restrictions. In heterogeneous multiprocessor systems, task and schedule assignments significantly impact the system's operation. Therefore, the different processes within the heuristic-based scheduling task algorithm will lead to a different makespan on a heterogeneous computing system. Thus, a suitable algorithm for scheduling should set precedence efficiently for every subtask based on the resources required to reduce its makespan. This paper proposes a novel efficient scheduling task algorithm based on the coronavirus herd immunity optimizer algorithm to solve task scheduling problems in a cloud computing environment. The basic idea of this method is to use the advantages of meta-heuristic algorithms to get the optimal solution. We evaluate the performance of our algorithm by applying it to three cases. The collected findings suggest that the proposed strategy successfully achieved the best solution in terms of makespan, speedup, efficiency, and throughput compared to others. Furthermore, the results demonstrate that the suggested technique beats existing methods new genetic algorithm (NGA), proposed particle swarm optimization (PPSO), whale optimization algorithm (WOA), enhanced genetic algorithm for task scheduling (EGA-TS), gravitational search algorithm (GSA), genetic algorithm (GA), and hybrid heuristic and genetic (HHG) by 22.8%, 12.3%, 8.8%, 7.3%, 7.3%, 3.4%, and 3.4% respectively according to makespan.

Keywords

Cloud Computing, Coronavirus Herd Immunity Optimizer Algorithm, Heterogeneous Processors, Task Scheduling.

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Ahmed Y. Hamed ¹, M. Kh. Elnahary ¹, Hamdy H. El-Sayed ¹

Affiliations
1 Faculty of Computers and Artificial Intelligence, Department of Computer Science, Sohag University, Sohag, 82524, EG

Abstract

In cloud computing systems, task scheduling is crucial. Task scheduling cannot be done based on a single criterion but rather on rules and regulations that may be referred to as an agreement between cloud customers and providers. This agreement is nothing more than the user's desire for the providers to offer the kind of service that they expect. Providing high-quality services to consumers under the deal is a critical duty for providers, who must also manage many responsibilities. The task scheduling problem may be considered the search for an ideal assignment or mapping of a collection of subtasks of distinct tasks across the available set of resources to meet the intended goals for tasks. This paper proposes an efficient scheduling task algorithm based on the social group optimization of cloud computing systems. By applying it to three cases, we evaluate the performance of our algorithm. The findings suggest that the proposed strategy successfully achieved the best solution in Makespan, Speedup, Efficiency, and Throughput.

Keywords

Heterogeneous resources, Social Group Optimization Algorithm, Task scheduling, Cloud Computing

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