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Design Issues, Models, and Simulation Platforms
Published in Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare, Energy Optimization Protocol Design for Sensor Networks in IoT Domains, 2023
Sanjeev J. Wagh, Manisha Sunil Bhende, Anuradha D. Thakare
Geographic routing: Geographic routing is based on greedy forwarding of local information on the topology of networks to route packets. The greedy perimeter stateless routing (GPSR) for MANETs is proposed by Karp et al. [1]. The protocol begins in greedy furthering mode and assumes that sensor node locale information can be achieved across systems [2,3]. By using perimeter roughing mode and the right-hand law, GPSR recovers from the local maximum location. Kranakis et al. [4] propose an algorithm for compass routing and FACE-1 which ensures destination is achieved even in greedy transfers, if the local minimum phenomenon occurs as in [4], the FACE-2 routing algorithm is proposed by Bose et al. [5]. Unlike GPSR, FACE-2 routing occurs across each node's perimeter of the Gabriel graph (GG). The FACE-1 often changes such that when the edge obstructs the line from the source to the target, the perimeter passes through the next edge.
Enabling Geo-centric Communication Technologies in Opportunistic Networks
Published in Hongjian Sun, Chao Wang, Bashar I. Ahmad, From Internet of Things to Smart Cities, 2017
Yue. Cao, D.e. Mi, Tong. Wang, Lei. Zhang
Geographic routing, also called position based routing, requires that each node can determine its own location and that the source is aware of the location of the destination. Different from topological routing concerning the network topology, geographic routing exploits the geographic information instead of topological connectivity information for message relay, to gradually approach and eventually reach the intended destination. According to Cao and Sun [4], it can be observed that previous routing protocols in ONs, mainly, have adopted historically topological information1 to predict the future encounter opportunity. In contrast, the focus of this chapter is to highlight the research vision and potential for applying geographic routing in ONs.
Adaptive Routing in Wireless Sensor Networks
Published in Mohamed Ibnkahla, Adaptation and Cross Layer Design in Wireless Networks, 2018
Hong Luo, Guohua Zhang, Yonghe Liu, Sajal K. Das
Position-based routing algorithms belong to geographic routing that utilizes knowledge of the geographic locations of the final destination and neighboring nodes. In these schemes, packets are routed geographically toward the destination through a relay node that offers progress toward the final destination. A simple criterion to select the next-hop relay is to find a neighbor that is located closest to the destination. Without considering channel state information, a relay node with unfavorable channel condition can be chosen. If channel state information is available to a forwarding node, it is possible for it to combat channel variations by exploiting diversity among the channels to different neighboring nodes.
Comparison of QoS optimisation techniques in adaptive smart device peer-to-peer overlay networks
Published in International Journal of Parallel, Emergent and Distributed Systems, 2021
Ananda Maiti, Andrew Maxwell, Alexander Kist
Each site has a different population size and the probability of nodes’ joining form them is considered directly proportional to the population. Geographic routing principles [29] aim to deliver packets or data governed at least partially by the geographic data of source, destination, and intermediate nodes. In this clustering approach, the cluster regions may be used in two ways: If the system needs one single operating central NDC, such as for authentication, introductory look-up tracker node etc., the clusters heads may be considered as representative sites for all sites with the cluster and the NDC may be determined.If the system operates with a series of NDCs operating in a P2P manner, the cluster heads q ∈ Qi can become the local NDC node for each cluster and each of them relays the data on behalf of their respective clusters’ nodes.