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Improving 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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 Publication date 2021
and research's language is العربية
 Created by Ammar Ghareeb




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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.


Artificial intelligence review:
Research summary
تتناول هذه الورقة البحثية تحسين أداء بروتوكول OLSR الاستباقي في الشبكات النقالة تلقائية التشكيل (MANETs) باستخدام خوارزمية مستعمرة النمل (ACO). تعتبر الشبكات النقالة تلقائية التشكيل شبكات ديناميكية تتغير طوبولوجيتها باستمرار بسبب حركة العقد. يركز البحث على تقليل التأخير الزمني وزيادة نسبة تسليم الرزم من خلال اختيار أفضل مسار للتوجيه بناءً على طول المسار وانشغالية العقد. تم استخدام المحاكي NS2.35 لاختبار الأداء في سيناريوهات مختلفة تتضمن زيادة عدد العقد وسرعة حركتها. أظهرت النتائج تحسنًا في تقليل التأخير الزمني وزيادة نسبة تسليم الرزم، ولكن مع زيادة في نسبة الفائض بسبب زيادة رسائل التحكم.
Critical review
دراسة نقدية: تقدم الورقة البحثية تحسينًا مهمًا في أداء بروتوكول OLSR باستخدام خوارزمية مستعمرة النمل، مما يساهم في تقليل التأخير الزمني وزيادة نسبة تسليم الرزم. ومع ذلك، يمكن أن تكون هناك بعض النقاط التي تحتاج إلى مزيد من الدراسة. على سبيل المثال، زيادة نسبة الفائض قد تؤثر سلبًا على أداء الشبكة في البيئات ذات الموارد المحدودة. كما أن الاعتماد على خوارزمية واحدة قد لا يكون كافيًا لتحسين جميع جوانب الأداء، ومن الممكن دراسة استخدام خوارزميات هجينة لتحقيق نتائج أفضل. بالإضافة إلى ذلك، يمكن أن تكون هناك حاجة لدراسة تأثير العوامل البيئية مثل الضجيج والتداخل على أداء البروتوكول المحسن.
Questions related to the research
  1. ما هو الهدف الرئيسي من البحث؟

    الهدف الرئيسي هو تحسين أداء بروتوكول OLSR الاستباقي في الشبكات النقالة تلقائية التشكيل من خلال تقليل التأخير الزمني وزيادة نسبة تسليم الرزم باستخدام خوارزمية مستعمرة النمل.

  2. ما هي العوامل الأساسية التي تم الاعتماد عليها لتقييم المسارات؟

    العوامل الأساسية هي طول المسار وانشغالية العقد الموجودة ضمن المسار.

  3. ما هي الأدوات المستخدمة لاختبار أداء البروتوكول المحسن؟

    تم استخدام المحاكي NS2.35 لاختبار أداء البروتوكول المحسن.

  4. ما هي النتائج الرئيسية التي توصل إليها البحث؟

    أظهرت النتائج تقليل التأخير الزمني وزيادة نسبة تسليم الرزم، ولكن مع زيادة في نسبة الفائض بسبب زيادة رسائل التحكم.


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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