An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper

Multi-layer virtual transport network management

Nowadays there is an increasing need for a general paradigm which can simplify network management and further enable network innovations. Software Defined Networking (SDN) is an efficient way to make the network programmable and reduce management complexity, however it is plagued with limitations inherited from the legacy Internet (TCP/IP) architecture. In this paper, in response to limitations of current Software Defined Networking (SDN) management solutions, we propose a recursive approach to enterprise network management, where network management is done through managing various Virtual Transport Networks (VTNs) over different scopes (i.e., regions of operation). Different from the traditional virtual network model which mainly focuses on routing/tunneling, our VTN provides communication service with explicit Quality-of-Service (QoS) support for applications via transport flows, and it involves all mechanisms (e.g., addressing, routing, error and flow control, resource allocation) needed to support such transport flows. Based on this approach, we design and implement a management architecture, which recurses the same VTN-based management mechanism for enterprise network management. Our experimental results show that our management architecture achieves better performance.National Science Foundation awards: CNS-0963974 and CNS-1346688

An agent-based approach to assess drivers’ interaction with pre-trip information systems.

This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’ responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing us to represent many of the mental aspects involved in the deliberation process