GAER: genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks
TL;DR: A novel routing protocol named genetic algorithm-based energy-efficient routing (GAER) protocol for infrastructure-less Oppnets is proposed, which uses a node’s personal information, and then applies the genetic algorithm (GA) to select a better next hop among a group of neighbour nodes for the message to be routed to the destination.
Abstract: In infrastructure-less opportunistic networks (Oppnets), the routing of messages is a challenging task since nodes are not aware of the network topology and they look for an opportunity to send the message by finding or predicting a best temporary path at each hop towards the destination. As nodes perform various computations for next hop selection, a lot of battery power gets consumed, which in turn reduces the network lifetime. Thus, there is a clear demand for routing protocols for such networks which are energy-efficient and consume lesser power of nodes in forwarding a message. In this paper, a novel routing protocol named genetic algorithm-based energy-efficient routing (GAER) protocol for infrastructure-less Oppnets is proposed. This protocol uses a node's personal information, and then applies the genetic algorithm (GA) to select a better next hop among a group of neighbour nodes for the message to be routed to the destination. With the application of GA, optimal results are obtained that help in the selection of the best possible node as the next hop, which in turn, leads to prolonged battery life. Simulation results show that GAER outperforms the Epidemic, PROPHET, and Spray and Wait protocols in terms of messages delivered, overhead ratio, average residual energy, and number of dead nodes. The results obtained for average latency and average buffer time using GAER are comparable to those obtained for the aforementioned protocols.
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TL;DR: The existing state-of-the-art in wireless sensor networks for agricultural applications is reviewed thoroughly and various case studies to thoroughly explore the existing solutions proposed in the literature in various categories according to their design and implementation related parameters.
627 citations
Cites background from "GAER: genetic algorithm-based energ..."
...…et al., 2014; Qu et al., 2014; Misra et al., 2013; Riquelme et al., 2009; Garcia-Sanchez et al., 2011; Camilli et al., 2007) are being applied in this domain to provide an optimal alternative to gather and process information (Behzadan et al., 2014; Dhurandher et al., 2014) to enhance productivity....
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23 Mar 2016
TL;DR: This paper proposes a novel routing protocol called Encounter and Distance based Routing (EDR), which utilizes the so-called forward parameter to determine the next hop selection, calculated by taking into account the number of encounters and the distance of each node in the network with respect to a particular destination.
Abstract: In an Opportunistic Network (Oppnet), the transmission of messages between mobile devices is achieved in a store-carry-and-forward fashion since nodes store the incoming messages in their buffer and wait until a suitable next hop node is encountered that can carry the message closer to the destination In such environment, due to the delay-tolerant nature of the network, designing a routing protocol is a challenge This paper proposes a novel routing protocol called Encounter and Distance based Routing (EDR), which utilizes the so-called forward parameter to determine the next hop selection This parameter is calculated by taking into account the number of encounters and the distance of each node in the network with respect to a particular destination Simulation results are provided, showing the superiority of EDR over the History based Prediction for Routing (HBPR) protocol and the ProWait protocol, chosen as benchmark schemes, in terms of hop count, messages dropped, and average latency
36 citations
01 Aug 2017
TL;DR: A new routing protocol called K-Nearest Neighbour based Routing protocol (KNNR) is proposed which judicially forwards the message through intermediate nodes towards the destination and efficiently reduces average latency, overhead ratio and average hop count while at the same time increases the message delivery probability.
Abstract: Opportunistic Networks (OppNets) are an extension of Mobile Adhoc Networks (MANETs), where no assumption is made regarding the preexistent path between the source and the destination node Hence, the nodes in OppNets are required to rely upon intermediate nodes for successful message delivery Therefore, the biggest challenge in OppNets for a carrier node is to make a decision whether the neighbour node will be a good carrier for the message in the future or not Hence, in this paper a new routing protocol called K-Nearest Neighbour based Routing protocol (KNNR) is proposed which judicially forwards the message through intermediate nodes towards the destination The proposed protocol initially stores the past behaviour of nodes in a dataset Whenever a decision has to be made related to an intermediate node, the protocol studies this dataset and finds instances that closely resemble the intermediate node based on their network parameters using K-Nearest Neighhbour (KNN) algorithm To evaluate the efficiency of the proposed protocol simulation results are compared with the existing routing protocols ie Epidemic, HBPR and ProPHET It was observed that the KNNR protocol efficiently reduces average latency, overhead ratio and average hop count while at the same time increases the message delivery probability
34 citations
Cites background from "GAER: genetic algorithm-based energ..."
...In OppNets, nodes are always moving which makes the network easy to deploy and decreases the dependence on infrastructure for communication [4]....
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01 Jan 2016
TL;DR: This survey paper reviews the main work presented for each type of mobile multihop ad hoc network and presents some innovative ideas and open challenges to guide further research in this topic.
Abstract: Evolutionary algorithms are metaheuristic algorithms that provide quasioptimal solutions in a reasonable time. They have been applied to many optimization problems in a high number of scientific areas. In this survey paper, we focus on the application of evolutionary algorithms to solve optimization problems related to a type of complex network like mobile multihop ad hoc networks. Since its origin, mobile multihop ad hoc network has evolved causing new types of multihop networks to appear such as vehicular ad hoc networks and delay tolerant networks, leading to the solution of new issues and optimization problems. In this survey, we review the main work presented for each type of mobile multihop ad hoc network and we also present some innovative ideas and open challenges to guide further research in this topic.
31 citations
Cites methods from "GAER: genetic algorithm-based energ..."
...[43] DTN Genetic algorithm; single objective Data dissemination To maximize packet delivery...
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...[43] S. K. Dhurandher, D. K. Sharma, I. Woungang, R. Gupta, and S. Garg, “GAER: genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks,” The Journal of Supercomputing, vol. 69, no. 3, pp. 1183–1214, 2014....
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...Another data dissemination technique for DTNs that uses genetic algorithms is GAER [43]....
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...Similarly to GAER, this solution also has the drawback of being computed at every contact....
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...In addition, GAER assumes that a node is connected tomultiple other nodes at the same time, but this is not the case in sparse networks (typical situation in DTNs)....
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20 Jul 2015
TL;DR: A new routing protocol named as PRoWait has been designed which can overcome the shortcomings of the already existing protocols in Oppnets and incorporates the merits of existing protocol so that it can be reliable and efficient for the communication of pedestrians with handheld devices.
Abstract: Opportunistic networks (Oppnet) are challenged networks in present wireless communication scenario. These networks are mainly applied to situations where a persistent end-to-end path between the source and the destination does not exist. Delay/Disruption Tolerant Networking (DTN) is mostly used to solve this end-toend path problem in such networks. Many routing protocols have been proposed in literature that consider various performance metrics such as delivery delay, packet delivery rate, hop count, among others. In this paper, a new routing protocol named as PRoWait has been designed which can overcome the shortcomings of the already existing protocols in Oppnets. The proposed protocol also incorporates the merits of existing protocol so that it can be reliable and efficient for the communication of pedestrians with handheld devices. Simulation results obtained for the proposed scheme show better performance as compared to the Porphet, Spray and Wait and Epidemic routing protocols in terms of packets delivery probability, overhead ratio, and hop count performance metrics.
28 citations
Cites background from "GAER: genetic algorithm-based energ..."
...…been designed in the past in Oppnets such as Epidemic (Vahdat, 2000), Spray and Wait (Spyropoulos et al., 2005), Binary Spray and Wait (Spyropoulos et al., 2005), Prophet (Lindgren et al., 2003), HBPR (Dhurandher et al., 2013) (Dhurandher et al, 2014), GAER (Dhurandher et al, 2014), among others....
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References
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Book•
01 Jan 1996TL;DR: An Introduction to Genetic Algorithms focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues.
Abstract: From the Publisher:
"This is the best general book on Genetic Algorithms written to date. It covers background, history, and motivation; it selects important, informative examples of applications and discusses the use of Genetic Algorithms in scientific models; and it gives a good account of the status of the theory of Genetic Algorithms. Best of all the book presents its material in clear, straightforward, felicitous prose, accessible to anyone with a college-level scientific background. If you want a broad, solid understanding of Genetic Algorithms -- where they came from, what's being done with them, and where they are going -- this is the book.
-- John H. Holland, Professor, Computer Science and Engineering, and Professor of Psychology, The University of Michigan; External Professor, the Santa Fe Institute.
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues.
The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines.
An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text.
The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
9,933 citations
01 Jan 2000
TL;DR: This work introduces Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery and achieves eventual delivery of 100% of messages with reasonable aggregate resource consumption in a number of interesting scenarios.
Abstract: Mobile ad hoc routing protocols allow nodes with wireless adaptors to communicate with one another without any pre-existing network infrastructure. Existing ad hoc routing protocols, while robust to rapidly changing network topology, assume the presence of a connected path from source to destination. Given power limitations, the advent of short-range wireless networks, and the wide physical conditions over which ad hoc networks must be deployed, in some scenarios it is likely that this assumption is invalid. In this work, we develop techniques to deliver messages in the case where there is never a connected path from source to destination or when a network partition exists at the time a message is originated. To this end, we introduce Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery. The goals of Epidemic Routing are to: i) maximize message delivery rate, ii) minimize message latency, and iii) minimize the total resources consumed in message delivery. Through an implementation in the Monarch simulator, we show that Epidemic Routing achieves eventual delivery of 100% of messages with reasonable aggregate resource consumption in a number of interesting scenarios.
4,355 citations
"GAER: genetic algorithm-based energ..." refers background or methods in this paper
...Examples of such type of protocols are Epidemic routing [15], PROPHET [16], Spray and Wait [17], and HiBOp [18], etc....
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...The Epidemic routing protocol [15] is a flooding-based routing technique....
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25 Aug 2003
TL;DR: This work proposes a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources.
Abstract: The highly successful architecture and protocols of today's Internet may operate poorly in environments characterized by very long delay paths and frequent network partitions. These problems are exacerbated by end nodes with limited power or memory resources. Often deployed in mobile and extreme environments lacking continuous connectivity, many such networks have their own specialized protocols, and do not utilize IP. To achieve interoperability between them, we propose a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources. The architecture operates as an overlay above the transport layers of the networks it interconnects, and provides key services such as in-network data storage and retransmission, interoperable naming, authenticated forwarding and a coarse-grained class of service.
3,511 citations
"GAER: genetic algorithm-based energ..." refers background in this paper
...Thus, Oppnets can bear longer message delivery delays and are considered as the subclass of delay-tolerant networks (DTNs) [10,11]....
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22 Aug 2005
TL;DR: A new routing scheme, called Spray and Wait, that "sprays" a number of copies into the network, and then "waits" till one of these nodes meets the destination, which outperforms all existing schemes with respect to both average message delivery delay and number of transmissions per message delivered.
Abstract: Intermittently connected mobile networks are sparse wireless networks where most of the time there does not exist a complete path from the source to the destination. These networks fall into the general category of Delay Tolerant Networks. There are many real networks that follow this paradigm, for example, wildlife tracking sensor networks, military networks, inter-planetary networks, etc. In this context, conventional routing schemes would fail.To deal with such networks researchers have suggested to use flooding-based routing schemes. While flooding-based schemes have a high probability of delivery, they waste a lot of energy and suffer from severe contention, which can significantly degrade their performance. Furthermore, proposed efforts to significantly reduce the overhead of flooding-based schemes have often be plagued by large delays. With this in mind, we introduce a new routing scheme, called Spray and Wait, that "sprays" a number of copies into the network, and then "waits" till one of these nodes meets the destination.Using theory and simulations we show that Spray and Wait outperforms all existing schemes with respect to both average message delivery delay and number of transmissions per message delivered; its overall performance is close to the optimal scheme. Furthermore, it is highly scalable retaining good performance under a large range of scenarios, unlike other schemes. Finally, it is simple to implement and to optimize in order to achieve given performance goals in practice.
2,712 citations
"GAER: genetic algorithm-based energ..." refers background in this paper
...The Spray and Wait protocol [17] is an improvement of the Epidemic routing protocol in the sense that it is designed to control the amount of flooding in the network by sending the message copy to only a limited number of nodes....
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...Examples of such type of protocols are Epidemic routing [15], PROPHET [16], Spray and Wait [17], and HiBOp [18], etc....
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TL;DR: A probabilistic routing protocol for intermittently connected networks where there is no guarantee that a fully connected path between source and destination exist at any time, rendering traditional routing protocols unable to deliver messages between hosts.
Abstract: We consider the problem of routing in intermittently connected networks. In such networks there is no guarantee that a fully connected path between source and destination exist at any time, rendering traditional routing protocols unable to deliver messages between hosts. We propose a probabilistic routing protocol for such networks.
2,530 citations