Design of hierarchical communication networks under node/link failure constraints

Saha, Debashis; Mukherjee, Amitava

doi:10.1016/0140-3664(95)96839-i

Cited by 14 publications

(3 citation statements)

References 13 publications

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“…Because of the expansive growth of the available capabilities in telecommunications it is expected that many services that today are provided by Scalability (see, e.g., (Gauthier, 1996), (Lin, 1994), (Martini, 1996), (Saha, 1995» is one of the most important factors in the design of a distributed multimedia system, such as B-IN. The system must be able to sustain a large number of users and various types of services with different traffic characteristics and Quality of Service (QoS) requirements.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation of Scalability in Broadband Intelligent Networks

Karagiannis

Nicola

Niemegeers

1998

Performance of Information and Communication Systems

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Scalability is the ability of a network to maintain the quality of service while increasing certain parameters relating to the size of the network, such as the number of users, the number of network nodes, the number of services provided, geographical spread, etc. In the design of a B-IN signalling systl>m, network scalability is an important issue that must be taken into account. In this paper we use simulation to investigate scalability issues related to a Broadband Intelligent Network (B-IN), such as that being considered in the ACTS project INSIGNIA. In particular, we study the impact of processor speed and configuration (in B-IN physical entities) on signalling performance. As signalling performance measures we consider the mean call setup delay of a B-IN service request and the network throughput. For Broadband Virtual Private Network (B-VPN) service, we perform scalability experiments by increasing some of the network parameters such as the number of users and the number of nodes.

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Section: Introductionmentioning

confidence: 99%

Quantitative Evaluation of Scalability in Broadband Intelligent Networks

Karagiannis

Nicola

Niemegeers

1998

Performance of Information and Communication Systems

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“…The BSs within an LA talk with each other through a Mobile Switching Center (MSC) for that LA. This can be referred to as intra-cluster communication [6]. On the other hand, inter-cluster communication [6] involves two cells which belong to two different clusters and hence are connected to different MSCs.…”

Section: Introduction -mentioning

confidence: 99%

“…This can be referred to as intra-cluster communication [6]. On the other hand, inter-cluster communication [6] involves two cells which belong to two different clusters and hence are connected to different MSCs. Each LA is, thus, serviced by a single MSC that is collocated in the Signaling Points (SPs) of the CCS network.…”

Section: Introduction -mentioning

confidence: 99%

CALB: a new cell-to-switch assignment algorithm with load balancing in the design of a personal communication services network (PCSN)

Bhattacharjee

Saha²,

Mukherjee³

2000 IEEE International Conference on Personal Wireless Communications. Conference Proceedings (Cat. No.00TH8488)

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This work deals with the problem of balancing traffic (load) amongst mobile switching centers (MSCs) when the cluster of cells to be connected to an MSC is decided during the design of a Personal Communication Services Network (PCSN). Our aim is to assign cells to MSCs in such a manner that the traffic handling capacity of each of the MSCs is utilized uniformly, thereby precluding the possibility of unfairness in loading of MSCs. This, in tum, makes all the MSCs equally scaleable against the increase in either mobile user density or per user traffic. A conventional cell to switch assignment (CSA) algorithm attempts to optimize only the total cost, comprising cable cost and handoff cost, without taking into account the utilization of the traffic handling capacity of MSCs. To obviate this limitation, we propose a new CSA algorithm with load balancing (CALB) which emphasizes equally on the load balancing as well as on cost optimization. As shown in this work, CALB performs extremely well in balancing the traffic amongst the MSCs present in the network thereby helping in increasing the overall scalability of the system. Although, it outperforms CSA in terms of load balancing, it does so obviously at the expense of slightly increased total cost (i.e., the solution obtained is a sub optimal one in terms of cost only). But the increase in cost is never overwhelming (5%-14%) vis-&vis the improvement in the system scalability (0.5%-19%).

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