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Register a new userImproving the Performance of Proactive Protocols in Manets Networks Using Artificial Intelligence Algorithms
تحسين أداء البروتوكولات الاستباقية في الشبكات النقالة تلقائية التشكيل باستخدام خوارزميات الذكاء الصنعي
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Ammar Ghareeb( باحث )
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Ammar Ghareeb
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الشبكات النقالة تلقائية التشكيل هي عبارة عن شبكات دون بنية تحتية وهي قابلة للنشر والتكوين الذاتي بسرعة ولا تحتاج إلى دعم مركزي, تتكون الشبكات النقالة تلقائية التشكيل من مجموعة من العُقد المتنقلة التي تعمل كجهاز توجيه ومضيف في نفس الوقت و تكون قادرة على نقل حركة المرور من عقدة إلى أخرى , وتتحرك العُقد في الشبكة بسرعة وحركة عشوائية مما يسبب تغير مستمر في طوبولوجيا الشبكة. إن مسألة التوجيه في الشبكة واختيار المسار الأفضل بين العقد من أكثر الأمور التي تجذب انتباه الباحثين في مجال الشبكات النقالة وذلك بسبب أهمية عملية التوجيه وتأثيرها على أداء الشبكة وتشكل عملية التوجيه تحدياً كبيراً نتيجة محدودية التقنيات اللاسلكية المستخدمة وتغير الطوبولوجيا بشكل كبير نتيجة حركة العقد. تم التركيز في هذا البحث على تحسين أداء بروتوكول OLSR الاستباقي من أجل اختيار المسار الأفضل للتوجيه الذي يحقق أقل نسبة تأخير زمني في الشبكة ويؤمّن أفضل نسبة تسليم للرزم خلال عملية الإرسال. تم استخدام خوارزمية مستعمرة النمل من أجل اختيار أفضل مسار بالاعتماد على عاملين أساسيين لتقييم المسارات وهما طول المسار و إنشغالية العقد الموجودة ضمن المسار, حيث تم بناء شبكة الشبكات النقالة تلقائية التشكيل باستخدام المحاكي NS2.35 وتم تنفيذ عدة سيناريوهات لاختبار أداء البروتوكول المحسن من حيث زيادة عدد العقد المتحركة في الشبكة وزيادة سرعة العقد المتحركة في الشبكة , وقد أظهرت نتائج الاختبار تقليل التأخير الزمني في الشبكة وزيادة نسبة تسليم الرزم.
Mobile Ad-Hoc Networks (MANETs) are infrastructure-less networks that are rapidly deployable and self-configuring and do not need central support. MANETs consist of a group of mobile nodes that act either as a router or as a host. Nodes in these network move rapidly and randomly, causing a continuous change in network topology. The routing in the network and choosing the best path between nodes are major issues that attract the attention of researchers in the field of mobile networks, because of the importance of the routing process and its impact on network performance. This paper focuses on improving the performance of the proactive OLSR protocol in order to choose the best routing path that achieves the least time delay in the network, secures the best packet delivery rate and ensures reducing packet loss during the transmission process. The ant colony algorithm was used to choose the best path based on two main factors , namely the path length and the occupancy of the nodes within the path. Our simulation scenarios are built using NS2.35 to test the performance of the improved protocol in terms of increasing the number of nodes in the network and increasing the speed of nodes in the network. The test results show a reduction in the time delay in the network and an increase in the packet delivery rate.
References used
Sirisala,S. ; Ramakrishna,S. Survey: Enhanced Trust Management for Improving QoS in MANETs. First International Conference on Artificial Intelligence and Cognitive Computing India. Vol 2,2018, p 255–263
Gautam, G. and Sen, B., 2015. Design and simulation of wireless sensor network in NS2. International Journal of Computer Applications, 113(16).
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We will see in the following study:
•The importance of wireless sensor networks and their applications
•The importance of quality of service in particular، reducing energy consumption
•The need for a simple routing protocol that minimizes energy consumption as much as possible، and we will count on LEACH
•Improve the quality of service offered by the LEACH protocol by studying several scenarios for improvement
Real-time multimedia transport over MANET has stringent bandwidth, delay, and loss requirements. It is
a great challenge to support such applications in wireless ad hoc networks, which are characterized by
frequent link failures, congestion, and lack of central administration.
In this research we are studying the possibility of contributing in
solving the problem of the Traveling Salesman Problem, which is
a problem of the type NP-hard . And there is still no algorithm
provides us with the Optimal solution to this problem . All the
algorithms used to give solutions which are close to the optimal
one .
We study in this paper the possibility of contribution in solving the vehicle routing problem (VRP) by using the improved ant colony system ( IACS) , which is one of the optimization problems that, because of its Real Life applications, has attracted
a lot of attention at the present time. It is a problem of the NP-hard type. However, because of the complication of polynomial time there is still no algorithm providing us with the optimal solution of this problem. All the used algorithms give solutions that are close to the optimal one .
We present the improved ant colony system algorithm that, based on ant colony system algorithm, possesses a new state transition rule, a new pheromone updating rule and diverse local search approaches .
The experimental results of the proposed ( IACS) algorithm compared with the results of well-known standard tests show that our IACS yields better solutions than the other ant algorithms in the literature and is competitive with other meta-heuristic approaches in terms of quality(run time and number of good solutions ).
n this research, we are studying the possibility of contribution in solving the Vehicle Routing Problem (VRP), which is one of the optimization problems that, because of its Real Life applications, has attracted a lot of attention at the present tim
e. It is a problem of the NP-hard type. However, because of the complication of polynomial time there is still no algorithm providing us with the optimal solution of this problem. All the used algorithms give solutions that are close to the optimal one .
In this research, we will present the Hybrid Algorithm (HA) in two phases .In the first phase the Sweep Algorithm (SW) is applied, and in the second one the Ant Colony Algorithm and the local search 3-opt are applied. we will then compare the quality of the solution resulted from this hybrid approach with the results of well-known standard tests to determine the effectiveness of the presented approach .
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