Pub Date : 2013-05-31DOI: 10.4018/978-1-61350-092-7.ch005
Feng Gu, Julie Greensmith, U. Aickelin
As one of the solutions to intrusion detection problems, Artificial Immune Systems (AIS) have shown their advantages. Unlike genetic algorithms, there is no one archetypal AIS, instead there are four major paradigms. Among them, the Dendritic Cell Algorithm (DCA) has produced promising results in various applications. The aim of this chapter is to demonstrate the potential for the DCA as a suitable candidate for intrusion detection problems. We review some of the commonly used AIS paradigms for intrusion detection problems and demonstrate the advantages of one particular algorithm, the DCA. In order to clearly describe the algorithm, the background to its development and a formal definition are given. In addition, improvements to the original DCA are presented and their implications are discussed, including previous work done on an online analysis component with segmentation and ongoing work on automated data preprocessing. Based on preliminary results, both improvements appear to be promising for online anomaly-based intrusion detection.
{"title":"The Dendritic Cell Algorithm for Intrusion Detection","authors":"Feng Gu, Julie Greensmith, U. Aickelin","doi":"10.4018/978-1-61350-092-7.ch005","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.ch005","url":null,"abstract":"As one of the solutions to intrusion detection problems, Artificial Immune Systems (AIS) have shown their advantages. Unlike genetic algorithms, there is no one archetypal AIS, instead there are four major paradigms. Among them, the Dendritic Cell Algorithm (DCA) has produced promising results in various applications. The aim of this chapter is to demonstrate the potential for the DCA as a suitable candidate for intrusion detection problems. We review some of the commonly used AIS paradigms for intrusion detection problems and demonstrate the advantages of one particular algorithm, the DCA. In order to clearly describe the algorithm, the background to its development and a formal definition are given. In addition, improvements to the original DCA are presented and their implications are discussed, including previous work done on an online analysis component with segmentation and ongoing work on automated data preprocessing. Based on preliminary results, both improvements appear to be promising for online anomaly-based intrusion detection.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123420929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.4018/978-1-61350-092-7.CH010
E. Varga, Bernát Wiandt, B. K. Benko, V. Simon
While traditional telecommunication still relies on rigid, highly regulated and highly controlled communication protocols, with the emergence of new forms of networks (mobile ad hoc and delaytolerant networks, lacking central infrastructure and strict regulations) bio-inspired communication protocols have also found their way to success. In this chapter we introduce a nontraditional way of creating and shaping communication protocols, through an autonomous machine intelligence model, built upon on-line evolutionary methods such as natural selection and genetic programming. Creating a genetic programming language and a selection mechanism for multi-hop broadcast protocols in ad hoc networks, we show that this kind of approach can outperform traditional ones under given circumstances, offering a powerful alternative in the future.
{"title":"Autonomously Evolving Communication Protocols","authors":"E. Varga, Bernát Wiandt, B. K. Benko, V. Simon","doi":"10.4018/978-1-61350-092-7.CH010","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH010","url":null,"abstract":"While traditional telecommunication still relies on rigid, highly regulated and highly controlled communication protocols, with the emergence of new forms of networks (mobile ad hoc and delaytolerant networks, lacking central infrastructure and strict regulations) bio-inspired communication protocols have also found their way to success. In this chapter we introduce a nontraditional way of creating and shaping communication protocols, through an autonomous machine intelligence model, built upon on-line evolutionary methods such as natural selection and genetic programming. Creating a genetic programming language and a selection mechanism for multi-hop broadcast protocols in ad hoc networks, we show that this kind of approach can outperform traditional ones under given circumstances, offering a powerful alternative in the future.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125881954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH009
P. Antoniou, A. Pitsillides
Next generation communication networks are moving towards autonomous wireless infrastructures, as for example, Wireless Sensor Networks (WSNs), that are capable of working unattended under dynamically changing conditions. Over the last few years, WSNs are being developed towards a large number of multimedia streaming applications, e.g., video surveillance, traffic control systems, health monitoring, and industrial process control. However, WSNs face important limitations in terms of energy, memory and computational power. The uncontrolled use of limited resources in conjunction with the unpredictable nature of WSNs in terms of traffic load injection, wireless link capacity fluctuations and topology modifications (e.g. due to node failures) may lead to congestion. Congestion can cause deterioration of the offered quality of service (QoS). This study proposes a bio-inspired congestion control approach for WSNs streaming applications that necessitate controlled performance with graceful degradation. The proposed approach prevents congestion in WSNs by regulating the rate of each traffic flow based on the Lotka-Volterra population model. Performance evaluations reveal that the proposed approach achieves adaptability to changing traffic loads, scalability and fairness among flows, while providing graceful performance degradation as the offered load increases.
{"title":"Congestion Control in Wireless Sensor Networks based on the Lotka Volterra Competition Model","authors":"P. Antoniou, A. Pitsillides","doi":"10.4018/978-1-61350-092-7.CH009","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH009","url":null,"abstract":"Next generation communication networks are moving towards autonomous wireless infrastructures, as for example, Wireless Sensor Networks (WSNs), that are capable of working unattended under dynamically changing conditions. Over the last few years, WSNs are being developed towards a large number of multimedia streaming applications, e.g., video surveillance, traffic control systems, health monitoring, and industrial process control. However, WSNs face important limitations in terms of energy, memory and computational power. The uncontrolled use of limited resources in conjunction with the unpredictable nature of WSNs in terms of traffic load injection, wireless link capacity fluctuations and topology modifications (e.g. due to node failures) may lead to congestion. Congestion can cause deterioration of the offered quality of service (QoS). This study proposes a bio-inspired congestion control approach for WSNs streaming applications that necessitate controlled performance with graceful degradation. The proposed approach prevents congestion in WSNs by regulating the rate of each traffic flow based on the Lotka-Volterra population model. Performance evaluations reveal that the proposed approach achieves adaptability to changing traffic loads, scalability and fairness among flows, while providing graceful performance degradation as the offered load increases.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125806850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH013
S. Luo, Y. Sagduyu, Jason H. Li
Ant Colony Optimization (ACO) for biologically inspired networking introduces performance gains over classical routing solutions for Mobile Ad Hoc Networks (MANETs). However, the current ACO protocols involve significant amount of overhead and do not fully reflect the wireless interference effects in routing decisions. In ant routing, sources send out ant-based control packets for route discovery and path maintenance. Destinations can assist ant packets by disseminating scent messages to provide better guidance for route discovery and thus effectively reduce the protocol overhead. For that purpose, Scented Node Protocol (SNP) is introduced for interference-aware routing with novel scent diffusion and reinforcement mechanisms. The wireless link rates are measured by identifying the node pairs that are the most impacted by wireless interference, and network flows are routed to avoid severe interference effects among concurrent wireless transmissions. The throughput and overhead performance of SNP is evaluated through extensive realistic simulations for dynamic MANET environment. The resulting amount of overhead for scent and ant packets is also evaluated through the asymptotic analysis of scaling laws, as the network size grows, and through the dynamic analysis of the finite overhead constraint, by discussing the possible effects of local network coding on scent dissemination between neighbor nodes. Our results verify the throughput and overhead gains of biologically inspired SNP in wireless networks over the existing ACO and MANET routing protocols. DOI: 10.4018/978-1-61350-092-7.ch013
{"title":"Scented Node Protocol for MANET Routing","authors":"S. Luo, Y. Sagduyu, Jason H. Li","doi":"10.4018/978-1-61350-092-7.CH013","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH013","url":null,"abstract":"Ant Colony Optimization (ACO) for biologically inspired networking introduces performance gains over classical routing solutions for Mobile Ad Hoc Networks (MANETs). However, the current ACO protocols involve significant amount of overhead and do not fully reflect the wireless interference effects in routing decisions. In ant routing, sources send out ant-based control packets for route discovery and path maintenance. Destinations can assist ant packets by disseminating scent messages to provide better guidance for route discovery and thus effectively reduce the protocol overhead. For that purpose, Scented Node Protocol (SNP) is introduced for interference-aware routing with novel scent diffusion and reinforcement mechanisms. The wireless link rates are measured by identifying the node pairs that are the most impacted by wireless interference, and network flows are routed to avoid severe interference effects among concurrent wireless transmissions. The throughput and overhead performance of SNP is evaluated through extensive realistic simulations for dynamic MANET environment. The resulting amount of overhead for scent and ant packets is also evaluated through the asymptotic analysis of scaling laws, as the network size grows, and through the dynamic analysis of the finite overhead constraint, by discussing the possible effects of local network coding on scent dissemination between neighbor nodes. Our results verify the throughput and overhead gains of biologically inspired SNP in wireless networks over the existing ACO and MANET routing protocols. DOI: 10.4018/978-1-61350-092-7.ch013","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120920149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-4666-5125-8.CH002
T. Nakano
This chapter provides a brief review of molecular communication, a networking paradigm inspired by cell communication mechanisms. In molecular communication, information is encoded to and decoded from molecules, rather than electrons or electromagnetic waves. Molecular communication provides bio-compatible and energy-efficient solutions with massive parallelization at the nano-to-micro scale; it is expected to play a key role in a multitude of domains including health, the environment, and ICT (Information Communication Technology). Models and methods of molecular communication are also reviewed, and research challenges that need to be addressed for further advancement of the molecular communication paradigm are discussed.
{"title":"A Networking Paradigm Inspired by Cell Communication Mechanisms","authors":"T. Nakano","doi":"10.4018/978-1-4666-5125-8.CH002","DOIUrl":"https://doi.org/10.4018/978-1-4666-5125-8.CH002","url":null,"abstract":"This chapter provides a brief review of molecular communication, a networking paradigm inspired by cell communication mechanisms. In molecular communication, information is encoded to and decoded from molecules, rather than electrons or electromagnetic waves. Molecular communication provides bio-compatible and energy-efficient solutions with massive parallelization at the nano-to-micro scale; it is expected to play a key role in a multitude of domains including health, the environment, and ICT (Information Communication Technology). Models and methods of molecular communication are also reviewed, and research challenges that need to be addressed for further advancement of the molecular communication paradigm are discussed.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121333679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH007
A. Perna, P. Kuntz, G. Theraulaz, C. Jost
Social insect colonies build large net-like systems: gallery and trail networks. Many such networks appear to show near-optimal performance. Focusing on the network system inside termite nests we address the question how simple agents with probabilistic behaviour can control and optimize the growth of a structure with size several magnitude orders above their perceptual range. We identify two major classes of mechanisms: (i) purely local mechanisms, which involve the arrangement of simple motifs according to predetermined rules of behaviour and (ii) local estimation of global quantities, where sizes, lengths, and numbers are estimated from densities, concentrations, and traffic. Theoretical considerations suggest that purely local mechanisms work better during early network formation and are less likely to fall into local optima. On the contrary, estimation of global properties is only possible on functional networks and is more likely to work through pruning. This latter mechanism may contribute to restore network functionalities following unpredicted changes of external conditions or network topology. An analysis of the network properties of Cubitermes termite nests supports the role of both classes of mechanisms, possibly in interplay with environmental conditions acting as a template. DOI: 10.4018/978-1-61350-092-7.ch007
{"title":"From Local Growth to Global Optimization in Insect Built Networks","authors":"A. Perna, P. Kuntz, G. Theraulaz, C. Jost","doi":"10.4018/978-1-61350-092-7.CH007","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH007","url":null,"abstract":"Social insect colonies build large net-like systems: gallery and trail networks. Many such networks appear to show near-optimal performance. Focusing on the network system inside termite nests we address the question how simple agents with probabilistic behaviour can control and optimize the growth of a structure with size several magnitude orders above their perceptual range. We identify two major classes of mechanisms: (i) purely local mechanisms, which involve the arrangement of simple motifs according to predetermined rules of behaviour and (ii) local estimation of global quantities, where sizes, lengths, and numbers are estimated from densities, concentrations, and traffic. Theoretical considerations suggest that purely local mechanisms work better during early network formation and are less likely to fall into local optima. On the contrary, estimation of global properties is only possible on functional networks and is more likely to work through pruning. This latter mechanism may contribute to restore network functionalities following unpredicted changes of external conditions or network topology. An analysis of the network properties of Cubitermes termite nests supports the role of both classes of mechanisms, possibly in interplay with environmental conditions acting as a template. DOI: 10.4018/978-1-61350-092-7.ch007","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130421549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH011
Éderson Rosa Da Silva, P. R. Guardieiro
Delay and disruption tolerant networks (DTNs) have the capacity of providing data communication to remote and rural areas where current networking technology does not work well. In such challenging areas characterized by long duration partition, routing is a common problem. Anycast routing can be used for many applications in DTNs, and it is useful when nodes wish to send messages to at least one, and preferably only one, of the members in an anycast destination group. In this chapter, an anycast routing algorithm for DTNs based on genetic algorithms (GAs) is presented and analyzed. The GA is applied to find the appropriate combination of each path to comply with the delivery needs of the group of anycast sessions simultaneously. The routing algorithm based on GAs under consideration uses the concept of subpopulation to produce the next generation of the population, a limited number of solutions to be evaluated, and yields minimum delay in achieving a specified rate of delivery. Simulation results show that the studied GA-based anycast routing algorithm can produce good results.
{"title":"Application of Genetic Algorithms for Optimization of Anycast Routing in Delay and Disruption Tolerant Networks","authors":"Éderson Rosa Da Silva, P. R. Guardieiro","doi":"10.4018/978-1-61350-092-7.CH011","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH011","url":null,"abstract":"Delay and disruption tolerant networks (DTNs) have the capacity of providing data communication to remote and rural areas where current networking technology does not work well. In such challenging areas characterized by long duration partition, routing is a common problem. Anycast routing can be used for many applications in DTNs, and it is useful when nodes wish to send messages to at least one, and preferably only one, of the members in an anycast destination group. In this chapter, an anycast routing algorithm for DTNs based on genetic algorithms (GAs) is presented and analyzed. The GA is applied to find the appropriate combination of each path to comply with the delivery needs of the group of anycast sessions simultaneously. The routing algorithm based on GAs under consideration uses the concept of subpopulation to produce the next generation of the population, a limited number of solutions to be evaluated, and yields minimum delay in achieving a specified rate of delivery. Simulation results show that the studied GA-based anycast routing algorithm can produce good results.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126270251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.4018/978-1-61350-092-7.CH008
S. De, S. Chatterjee
Scarcity of energy in tiny battery-powered wireless sensor nodes have led to a tremendous amount of research thrust at all protocol levels in wireless networks. Despite efficient design of the underlying communication protocols, limited battery energy primarily restricts the usage of nodes and hence the lifetime of the network. As a result, although there has been a lot of promise of pervasive networking via sensors, limited energy of the nodes has been a major bottleneck to deployment feasibility and cost of such a network. With this view, alongside many innovative network communication protocol research to increase nodal as well as network lifetime, there have been significant ongoing efforts on how to impart energy to the depleted batteries on-line. In this chapter, we propose to apply the lessons learnt from our surrounding nature and practices of the living world to realize network energy operated field sensors. We show that, although the regular communicating nodes may not benefit from network energy harvesting, by modifying the carrier sensing principle in a hierarchical network setting, the low power consuming field nodes can extend their lifetimes, or even the scavenged RF energy can be sufficient for the uninterrupted processing and transmission activities of the field nodes.
{"title":"Network Energy Driven Wireless Sensor Networks","authors":"S. De, S. Chatterjee","doi":"10.4018/978-1-61350-092-7.CH008","DOIUrl":"https://doi.org/10.4018/978-1-61350-092-7.CH008","url":null,"abstract":"Scarcity of energy in tiny battery-powered wireless sensor nodes have led to a tremendous amount of research thrust at all protocol levels in wireless networks. Despite efficient design of the underlying communication protocols, limited battery energy primarily restricts the usage of nodes and hence the lifetime of the network. As a result, although there has been a lot of promise of pervasive networking via sensors, limited energy of the nodes has been a major bottleneck to deployment feasibility and cost of such a network. With this view, alongside many innovative network communication protocol research to increase nodal as well as network lifetime, there have been significant ongoing efforts on how to impart energy to the depleted batteries on-line. In this chapter, we propose to apply the lessons learnt from our surrounding nature and practices of the living world to realize network energy operated field sensors. We show that, although the regular communicating nodes may not benefit from network energy harvesting, by modifying the carrier sensing principle in a hierarchical network setting, the low power consuming field nodes can extend their lifetimes, or even the scavenged RF energy can be sufficient for the uninterrupted processing and transmission activities of the field nodes.","PeriodicalId":222328,"journal":{"name":"Biologically Inspired Networking and Sensing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114390756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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