Saving Energy in Ad Hoc Wireless Networks
The objective of this study is to compare a research paper titled “Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks” (Chen et al. 2001) with a paper titled “Geography informed Energy Conservation for Ad Hoc Routing” (Xu et al., 2001). The study also compares other paper titled “Adaptive Energy-Conserving Routing for Multihop Ad Hoc Networks” with other research papers.
The paper provides the problem that each study solves to enhance the greater understanding of the problem associated with the wireless networking and the strategies the authors use to solve the problem.
Problem they solved
The problem that Xu at al (2001) attempt to solve is the problem of routing message overhead, packet loss and route length. The authors argue that ad-hoc network is often deployed using battery powered nodes. Thus, optimization of energy consumption is very critical for the efficient use of ad-hoc network and limited energy resources affect the lifetime, utility and overall performances of network resources. With the importance of energy use for the ad-hoc network, the authors reveals that nodes consume high energy during transmission making energy devices to be a major challenge. Xu et al. (2001) also identify the problem of energy costs due to the packet transmission. The authors solve the problem of energy loss by providing the ad hoc routing protocols such as AODV and DSR that consume lesser energy to enhance the performances and lifetime of the ad-hoc wireless network. Chen, et al. (2001) also solved the similar problem by minimizing the energy consumption in the mobile network. The author argues that minimizing energy consumption has become a challenge in the mobile networking. Thus, the authors develop Span to reduce energy consumption of the mobile networking as well as enhancing the performances of wireless networking.
Xu at al (2000) in their own case solve similar problem of loss rate and packet overhead in the ad-hoc networking. To solve the problem, the authors developed energy saving algorithms (AODV and DSR) that turn off the radio and improve the energy consumption.
Approach they took: Novelty
The authors take different approach to solve the problem. Xu et al. (2000) develop algorithms that turn off the radio in order to improve the power consumption. Typically, the author design energy saving algorithms to trade off the data delivery quality and energy conservation. To verify the validity of the energy saving algorithms, the authors carry out the stimulation to show that the energy-conserving algorithms consume as little as 50% of the energy. The author developed AFECA (adaptive fidelity energy-conserving algorithm) to increase the number of time the radio power off, and the goal of AFECA is to make the ad-hoc networking to perform better in term of packet loss than the prior ad-hoc networking developed.
Chen et al. (2001) in their case use Span to fulfill the energy conserving algorithms. The authors uses Span to adaptively coordinate all nodes in the network. Thus, the authors have been able to achieve the following goals using Span. First, Span continuously perform multi-hop-packet-routing within the ad-hoc network making the node to achieve power saving. Typically, all nodes have been able to provide global equal connectivity as well as minimizing the number of nodes elected as coordinator, which enhances the increase in the lifetime of the network. However, Xu et al. (2001) uses GAF to alleviate energy burden and keep a constant level of routing fidelity. The approach the authors use is the localization information using GPS or other methods to develop a rough network topology. From the topology, the authors divide surveyed area into the virtual grid cells with the node, which function equivalent to one another making GAF algorithm to work regardless of underlying protocol.
Chen et al. (2001) carry out the evaluation of Span using stimulation technique. The stimulation results reveal that Span not only outperform by enhancing power saving device, Span also extends network lifetime. Span is also able to save power in per-packet deliver latency and heavy load. Xu et al. (2000) also carry out the evaluation adaptive fidelity energy-conserving algorithm using stimulation method. The authors carry out the analytical evaluation in a restricted scenarios and the technique has been able to explore the performances of AFECA. To enhance the effectiveness of evaluation, the authors use the ns-2 simulator because it is able to support wide range of protocol, which include TORA, DSDV, DSR, and AODV. The results of performance evaluation reveal that AFECA is effective in enhancing the network lifetime. Additionally, the evaluation result reveal that AFECA has been able to achieve energy saving. Xu et al. (2001) carry out the evaluation of GAF using stimulation model. Unlike other energy saving algorithms devices, it is difficult to carry out GAF performance using the analytical model. Thus, the authors used the locally and extended version. The results of the evaluation performances reveal that GAF has been able to increase the network lifetime by 30% to 40% as well as saving energy by 40%.
Pros and Cons
Major benefit of the work is that all the authors have been able to demonstrate the strategies to reduce the power consumptions within the mobile networking and ad-hoc wireless networking thereby saving the enormous costs for the users. Moreover, the projects also reveal the strategies to increase the lifetime of the mobile networking to enhance the use of the mobile networking devices.
Despite the benefits derived from the work, the authors did not carry out the projects in a real world environment. All the works have been carried out using stimulation techniques to test the efficacy of the algorithms. The real benefits of the work could only be 100% valid if the authors carry out the experiment in a real life situation.
Method to improve the Work
The authors need to use a combination of stimulation technique and real world experiment to test the validity of the algorithms. The findings of the two experiments will assist the authors to understand the efficacy of the algorithms in a real world. The experiment carried out in a real world would reveal the effectiveness of energy saving algorithms developed by the authors.
The study carries out the comparison of the three research papers to enhance greater understanding on the strategies the authors use different energy saving algorithms for the wireless or mobile networking. Span is an energy power saving technique designed for the multi-hop wireless network. Span reduces the energy consumption without reducing connectivity and capacity of the network. Chen et al. (2001) describes Span as distributed randomized algorithms where nodes are designed to make local decisions to join forward backbone. The major objective for designing Span is to minimize the energy consumption in the mobile networking. Minimizing the energy consumption has become an important challenge within the networking environment. While significant progress has been made to reduce energy consumption for mobile devices, however, the power could be saved by turning off the radio when not in use. This approach is not very effective especially in control protocols and higher level routing. To address this problem, Chen et al. (2001) presents coordination of power saving using routing ad-hoc wireless network. A good power saving devices for wireless network ought to have the following features:
It must have as many nodes as possible to turn off the radio receiver off most of the time. Moreover, it needs to forward packets with source and destination with minimal delay. More importantly, the backbone should provide as many capacities as possible similar to the original network. Chen et al. (2001) argue that the Span algorithms fulfill the above listed conditions. Typically, each node within the network running Span participates in the forwarding backbone topology.
Similarly, GAF (geographical adaptive fidelity) is also an energy saving technique that assist in reducing energy consumption for the wireless network. Similar to Span, GAF conserve energy by identifying the nodes that are equivalent to the routing perspective and turn off unnecessary node. GAF has ability to moderate system level and application level information.
However, GAF uses the geographical location information to divide the world into the constant fixed square grip where the size of each grid is constant regardless of the density node. However, Span differs from GAF in two ways. First, unlike GAF, Span does not require nodes to identify the geographic position. On the other hand, Span uses broadcast messages to react and discover changes in the network topology. More importantly, Span integrates 802.11 power saving mode where non-coordinator node could receive packets.
Typically, GAF is an example of energy conserving system that assist wireless network to consume between less than 40% and 60% than other routing protocol. Xu et al. (2001) argues that nodes consume high energy during transmission and routing and reducing source of energy may affect energy saving within the network. However, the GAF alleviates energy burden for the network as well as distributing energy stress in order increase overall lifetime of the network. The strategy is to partition the network and distribute the routing of the entire group of node instead of only one node having full energy burden task.
Similar to the previous paper reviewed, Xu et al. (2000) in their paper titled “Adaptive Energy-Conserving Routing for Multihop Ad Hoc Networks” also develop two algorithms for routing energy saving devices. While other papers develop energy saving devices such as GAF and Span, Xu et al. (2000) develop AODV and DSR, which are the algorithms to reduce energy consumption in the application- level development. Similar to GAF that consume between 40% and 60% of less energy consumption, and Span, AODV and DSR have ability to consume as little as 50% of the energy in the ad-hoc routing protocol, which assist in increasing the network lifetime four-fold.
Geographical adaptive fidelity: The energy saving algorithms developed by Xu et al. (2001)
Adaptive Energy Conserving Routing: The energy saving algorithms developed by Xu et al. (2000).
Span: This is an energy saving algorithms developed by Chen (2001).
Chen, B. Jamieson, K. Balakrishnan, H. “Span: An energy-efficient saving coordination algorithm for topology maintenance in ad hoc wireless networks” ACM Wireless Networks Journal. (2001).
Xu, Y. Heidemann, J. & Estrin, D. Geography-informed Energy Conservation for Ad Hoc Routing. . ACM Wireless Networks Journal. .2001
Xu, Y. Heidemann, J. & Estrin, D. “Adaptive Energy for Routing Conserving for Multihop Ad Hoc Networks.” USC/ISI Research Report 527. .2000.
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