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    Organizing Named Data Objects in Distributed Name Resolution System for Information-Centric Networks
    (Springer International Publishing Ag, 2020) Elbrieki, Walid; Hassan, Suhaidi; Arlimatti, Shivaleela; Habbal, Adib
    The Information-centric Networks (ICN), an important research direction of the future Internet architecture, has gained lot of attention from the research community. The aim is to improve the current Internet with a new architecture where the design is completely based on information instead of the host. The information is named and is called as Named Data Object (NDO), utilized for data registration and name resolution, and the system that translates the object identifiers to network address is known as Name Resolution System (NRS). The random NRS distribution and network segregation are important and challenging issues in increasing NDO registration and storage. It is challenging for a single NRS to handle more than 10(15) expected NDO's with low latency and good throughput, along with the issues interest flooding and interest congestion. To overcome these problems NRS is distributed based on the location of routers. The mechanism is called Distributed Name Resolution Mechanism (DNRM). The NDO storage needs to be organized to increase the scalability of NRS. Distributed hash table and Bloom Filter have their own problems such as high latency in individual element searching and member deletion respectively. To overcome the above-mentioned issues the Balance Binary Tree (BBT) data structure is introduced to manage large NDO storage. The implementation results reduce the end-to-end delay by increasing network throughput. The contribution of this study is significant in promoting the use of NRS in ICN for handling the heterogeneity of the future Internet.
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    Software Defined Network Partitioning with Graph Partitioning Algorithms
    (Springer International Publishing Ag, 2020) Arlimatti, Shivaleela; Elbrieki, Walid; Hassan, Suhaidi; Habbal, Adib
    Software Defined Networks is an emerging paradigm in Internet communication world that increases the flexibility of today's networks by decoupling control plane and data plane of the network devices. The fundamental aim is to centralize the control and reduce the complexity of the networks. The communication medium between control and data plane is through OpenFlow protocol, an open standard network protocol designed to manage the network traffic by software programs. To increase the scalability and flexibility of controllers the OpenFlow controllers are distributed based on location and network types. However, most critical issue is minimizing the communication cost between the controller domains. In this paper, two graph partitioning algorithms Fiduccia-Matthyses algorithm and Kernighan-Lin algorithm are used to minimize the communication cost between distributed OpenFlow controller domains. The implementation of the algorithms is under Matlab simulation environment. The methodology used for the proposed algorithms is to interchange the elements from one domain to other domain to calculate the gain. The simulated results show that Kernighan-Lin algorithm minimizes more communication cost rather than the Fiduccia-Matthyses algorithm.