Designing Dependable Agent Systems for Mobile Wireless Networks

Cicirello, Vincent A.; Peysakhov, Maxim; Anderson, Gustave; Naik, Gaurav; Tsang, Kenneth; Regli, William C.; Kam, Moshe

doi:10.1109/mis.2004.41

Cited by 16 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, engineering research is profiting from and, to a certain extent, helping to drive advances in the understanding of collective decision-making. The house-hunting models mentioned above have already inspired the design of novel computer algorithms applicable to mobile ad hoc networks Cicirello et al 2005;Peysakhov et al 2006) and swarm robotics (Berman et al 2006;Berman et al 2007).…”

Section: Discussionmentioning

confidence: 99%

“…Such is the power and efficiency of this form of decision making that honey bees, for example, can select the best nest site even if news of it arrives late in the decision-making process (Seeley and Buhrman 1999; see also Britton et al 2002 for a mathematical model of this process). As with other social insect behaviors, house-hunting has also attracted the attention of engineers Cicirello et al 2005;Peysakhov et al 2006;Berman et al 2006Berman et al , 2007. In this paper, we will investigate experimentally if house-hunting T. albipennis ants can respond to new information that arrives late.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Moving targets: collective decisions and flexible choices in house-hunting ants

et al. 2007

View full text Add to dashboard Cite

Many decisions involve a trade-off between commitment and flexibility. We show here that the collective decisions ants make over new nest sites are sometimes sufficiently flexible that the ants can change targets even after an emigration has begun. Our findings suggest that, in this context, the ants' procedures are such that they can sometimes avoid 'negative information cascades' which might lock them into a poor choice. The ants are more responsive to belated good news of a higher quality nest than they are when the nest they had initially chosen degraded to become worse than an alternative. Our study confirms, in a new way, that ant colonies can be very powerful "search engines".

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Moving targets: collective decisions and flexible choices in house-hunting ants

et al. 2007

View full text Add to dashboard Cite

show abstract

“…This paper significantly improves the fidelity of an ecology-based model for managing agent populations on MANETs such as the Philadelphia Area Urban Wireless Network Testbed (PA-UWNT) [1], where ecology-based agents are being used in a real-worldenvironment.…”

Section: Discussionmentioning

confidence: 99%

Stability and control of agent ecosystems

Peysakhov

Lass

Regli

2005

Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

View full text Add to dashboard Cite

“…University's live MANET testbed [4,3]. It consists of dozens of mobile computing hosts-PDAs and tablets-on an 802.11b wireless network with ad-hoc routing.…”

Section: Embodied Experiments We Present Experiments Using Drexelmentioning

confidence: 99%

Quorum sensing on mobile ad-hoc networks

Peysakhov

Dugan

Modi

et al. 2006

Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems

View full text Add to dashboard Cite

Mobile ad-hoc networks (MANETs) are an increasingly important networking paradigm that will be the backbone of important defense and first response networks. Group decision-making is key to these environments, but is made difficult when MANETs are introduced due to network disruptions, bandwidth limitations, and host mobility patterns. Results gathered using standard group decisionmaking algorithms can become inaccurate, time-insensitive, or computationally undecidable. This paper focuses on a group decisionmaking approach using agent-based quorum sensing (ABQS) on MANETs. A mobile agent collects information (e.g., votes) from each host on a network until it can make an informed decision about global preference. This agent exploits the inherent tradeoff between efficient vote collection and result accuracy in order to provide better results, when considering survivability, hosts visited, hops made, and time spent, with only a very slight drop in correctnessbenefits that greatly outweigh costs. Experimental evidence from live MANETs demonstrates the effectiveness of this solution.

show abstract

Designing Dependable Agent Systems for Mobile Wireless Networks

Cited by 16 publications

References 3 publications

Moving targets: collective decisions and flexible choices in house-hunting ants

Moving targets: collective decisions and flexible choices in house-hunting ants

Stability and control of agent ecosystems

Quorum sensing on mobile ad-hoc networks

Contact Info

Product

Resources

About