A Heuristic Technique for Solving Dual-Homing Assignment Problem of 2.5G Cellular Networks

Sadhukhan, Samir K.; Mandal, Swarup; Saha, Debashis

doi:10.1109/iccta.2007.8

Cited by 6 publications

(5 citation statements)

References 13 publications

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“…The hacker travels from her present location within the MANET to the destination node and then returns after exploiting the target at the destination node. Therefore the mobility is diurnal (Sadhukhan et al 2010;Sadhukhan et al 2007). While no existing research has adopted direction-based diurnal mobility for vulnerable node determination in h-MANETs, several studies have used it in various other networks to determine transition probability.…”

Section: Routing Algorithms In Manetsmentioning

confidence: 99%

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A Markov-Based Model for Information Security Risk Assessment in Healthcare MANETs

et al. 2017

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Information security breaches are of major concern for healthcare mobile ad-hoc networks (h-MANETs). In this paper, we propose a model that identifies and assesses risk in an h-MANET deployed by a healthcare institution in a disasterprone region a priori by modeling the possible routes a hacker might follow to compromise a target. Our model proposes a novel method to compute the transition probability of each hop in the h-MANET. Next, it employs Markov theory to compute the maximum and minimum number of hops required to compromise the target for a given source-target pair. It then determines the vulnerability for all the paths comprising minimum to maximum hops only for each pair by computing their overall transition probability. Finally, our model computes the risk associated with each of these paths. Based on the calculated risk level of each path, the management can recommend an appropriate risk mitigation strategy.

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Section: Routing Algorithms In Manetsmentioning

confidence: 99%

“…The formula for obtaining the distance(dist) between two nodes having coordinates (i 0 , j 0 ) and (i k , j k ) in a non-orthogonal Cartesian system where the axes are inclined at 60°is shown in Eq. ( 5) and has been stated in (Sadhukhan et al 2007) as:…”

Section: Distance (D)mentioning

confidence: 99%

A Markov-Based Model for Information Security Risk Assessment in Healthcare MANETs

et al. 2017

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“…Researchers have traditionally formulated the NodeB-RNC (earlier known as cell-switch) assignment problem as a combinatorial op-timization problem and have solved it using meta-heuristics (Demrikoletl, 2001;Quintero & Pierre, 2002;Pierre & Houeto 2002;Dialloetl, 2006) or domain-specific heuristics (Merchant & Sengupta, 1995;Saha et al, 2000;Bhattacharjee et al, 2004;Mandal, Saha, & Mahanti, 2004, 2005. However, till date they all have considered single homing criteria, and have excluded the multi-homing scenario.…”

Section: Introductionmentioning

confidence: 99%

“…However, till date they all have considered single homing criteria, and have excluded the multi-homing scenario. Recently, we solved the dual homing of RNCs to MSCs in 2.5G networks with a suboptimal greedy algorithm (Sadhukhan et al, 2007) following the approach given in Din and Tseng (2002) which, however, deals with ATM networks (not cellular) and employs the meta-heuristic genetic algorithm (GA). The state space formulation of the problem was absent in (Sadhukhan et al, 2007), and, hence, we could not devise any domain specific heuristic there.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, we solved the dual homing of RNCs to MSCs in 2.5G networks with a suboptimal greedy algorithm (Sadhukhan et al, 2007) following the approach given in Din and Tseng (2002) which, however, deals with ATM networks (not cellular) and employs the meta-heuristic genetic algorithm (GA). The state space formulation of the problem was absent in (Sadhukhan et al, 2007), and, hence, we could not devise any domain specific heuristic there. In the current work, we have extended our earlier work to UMTS networks for dual homing of RNCs to MSCs/SGSNs and solved it using four separate techniques.…”

Section: Introductionmentioning

confidence: 99%

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Improving Quality of Experience of Subscribers through Post Deployment Network Planning in UMTS Cellular Networks

Sadhukhan

Mandal

2012

International Journal of Business Data Communications and Networking

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It is an established fact that cost of churning is a common concern for being profitable in the cellular network service provider’s space. Service providers can view this problem as a service management problem and can have a solution to enhance the stickiness of subscribers by managing the quality of user experience. Quality of Experience (QoE) is important in contrast to Quality of Service (QoS). Three basic components of service management are stage, prop, and user experience. In this cellular network service context, network infrastructure acts as prop. Prop needs to be flexible to enable the personalization in providing the service. In reality the major challenge for a service provider is keep the fitment between prop and the dynamic changes in subscriber profile in a cost effective manner. To define the problem more precisely, the authors take the conventional UMTS cellular network. Here, operators have considered single-homing of RNCs to MSCs/SGSNs (i.e., many-to-one mapping) with an objective to generate service at lower cost over a fixed period of time. However, a single-homing network does not remain cost-effective and flexible anymore when subscribers later begin to show specific inter-MSC/SGSN mobility patterns over time. This necessitates post-deployment topological extension of the network in which some specific RNCs are connected to two MSCs/SGSNs via direct links resulting in a more complex many-to-two mapping structure in parts of the network. The authors formulate the scenario as a combinatorial optimization problem and solve the NP-Complete problem using three meta-heuristic techniques, namely Simulated Annealing (SA), Tabu search (TS), and Ant colony optimization (ACO). They then compare these techniques with a novel optimal heuristic search method that the authors propose typically to solve the problem. The comparative results reveal that the search-based method is more efficient than meta-heuristic techniques in finding optimal solutions quickly.

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Post Deployment Planning of 3G Cellular Networks through Dual Homing of NodeBs

Sadhukhan

Mandal

Bhaumik

et al. 2010

Distributed Computing and Networking

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A Heuristic Technique for Solving Dual-Homing Assignment Problem of 2.5G Cellular Networks

Cited by 6 publications

References 13 publications

A Markov-Based Model for Information Security Risk Assessment in Healthcare MANETs

A Markov-Based Model for Information Security Risk Assessment in Healthcare MANETs

Improving Quality of Experience of Subscribers through Post Deployment Network Planning in UMTS Cellular Networks

Post Deployment Planning of 3G Cellular Networks through Dual Homing of NodeBs

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