Cost-Aware Handover Decision Algorithm for Cooperative Cellular Relaying Networks

Wu, Tong; Huang, Jun; Yu, Xiangbin; Qu, Xinchun; Wang, Ying

doi:10.1109/vetecs.2008.540

Cited by 12 publications

(5 citation statements)

References 7 publications

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“…Therefore, the cost optimization must be considered during a handover process. A scheme based on cost aware handover decision is proposed which uses two cost functions, that is, triggering and priority decision [24]. Both functions are optimized for the best values of signal transmission quality, handover signaling cost, handover latency, and estimate interference.…”

Section: Related Workmentioning

confidence: 99%

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Power Aware Mobility Management of M2M for IoT Communications

Ahmad

Paul

Rathore

et al. 2015

Mobile Information Systems

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Machine-to-Machine (M2M) communications framework is evolving to sustain faster networks with the potential to connect millions of devices in the following years. M2M is one of the essential competences for implementing Internet of Things (IoT). Therefore, various organizations are now focusing on enhancing improvements into their standards to support M2M communications. Thus, Heterogeneous Mobile Ad Hoc Network (HetMANET) can normally be considered appropriate for M2M challenges. These challenges incorporated when a mobile node (MN) selects a target network in an energy efficient scanning for efficient handover. Therefore, to cope with these constraints, we proposed a vertical handover scheme for handover triggering and selection of an appropriate network. The proposed scheme is composed of two phases. Firstly, the MNs perform handover triggering based on the optimization of the Receive Signal Strength (RSS) from an access point/base station (AP/BS). Secondly, the network selection process is performed by considering the cost and energy consumption of a particular application during handover. Moreover, if there are more networks available, then the MN selects the one provided with the highest quality of service (QoS). The decision regarding the selection of available networks is made on three metrics, that is, cost, energy, and data rate. Furthermore, the selection of an AP/BS of the selected network is made on five parameters: delay, jitter, Bit Error Rate (BER), communication cost, and response time. The numerical and experimental results are compared in the context of energy consumption by an MN, traffic management on an AP/BS, and QoS of the available networks. The proposed scheme efficiently optimizes the handoff related parameters, and it shows significant improvement in the existing models used for similar purpose.

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Section: Related Workmentioning

confidence: 99%

“…If an AP/BS reaches a close state, then it blocks any incoming connections. The probability of blocking a new connection can be represented as follows [24,35]:…”

Section: Mobile Information Systemsmentioning

confidence: 99%

Power Aware Mobility Management of M2M for IoT Communications

Ahmad

Paul

Rathore

et al. 2015

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…Therefore, the cost optimization must be considered during a handover process. A scheme based on cost aware handover decision is proposed which uses two cost functions, i.e., triggering and priority decision [22]. Both functions are optimized for the best values of signal transmission quality, handover signaling cost, the handover latency, and estimate interference.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Parameter Based Vertical Handover Decision Scheme for M2M Communications in HetMANET

Ahmad¹,

Rathore²,

Paul³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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The Machine-to-Machine (M2M) communication has the potential to connect millions of devices in the near future. Since they agree on this potential, several standard organizations need to focus on improved general architecture for M2M communications. Currently, there is a lack of consensus to improve the general feasibility of M2M communication. Heterogeneous Mobile Ad hoc Networks (HetMANETs) can normally be considered appropriate for M2M challenges. When a mobile node (MN) moves inside a HetMANET, various challenges including a selection of the target network and energy efficient scanning take place, which need to be addressed for efficient handover. To cope with these issues, we propose a handover management scheme that efficiently initiates a handover process and selects an optimal network. Our proposed scheme is composed of two phases, i.e., i) the MN performs handover triggering based on the optimization of the Receive Signal Strength (RSS) from an access point/base station (AP/BS), and, ii) the network selection process is carried out byconsidering different parameters such as delay, jitter, velocity, network load, and energy consumption by the network interface. Moreover, if there are more networks available, then the MN selects the one that can provide the highest quality-of-service (QoS) using the Elimination and Choice Expressing Reality (ELECTRE) decision model. The performance of the proposed scheme is compared in the context of the number of handovers, average stay-time of an MN in the network, and energy consumption against periodic and adaptive scanning. Similarly, a two-state Markov model is defined that efficiently distribute the number nodes on the available access points and base stations. The proposed scheme efficiently optimizes the handoff related parameters and outperforms existing schemes.

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“…A MU can enter the queue until there is free space in a handover queue or its estimated remaining time is less than estimated remaining time of aleast priority request in the queue [11]. While, In the heavy traffic networks, many MSs may send out HO requests to the same target at the same time leading to the performance degradation [14].…”

Section: Analysis Of the Handover Prioritiesmentioning

confidence: 99%

A New Proposed Algorithm for the Priority of the Cellular Calls

Awad¹

2012

ETJ

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There are many criteria for managing the priority in calling queues. The purpose of our work is to make a balance between two conflicting requirements: maximize the resource utilization and minimize the forced handover call dropping rate. This balance can be satisfied by using the dynamically manages of the priority criterion which is changed according to the current status of the hand off queue(remaining time(Tr) and rate of change of RSS (∆RSS)). The result is clear for reducing the blocking probability within range from 2% to 50%.

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Cost-Aware Handover Decision Algorithm for Cooperative Cellular Relaying Networks

Cited by 12 publications

References 7 publications

Power Aware Mobility Management of M2M for IoT Communications

Power Aware Mobility Management of M2M for IoT Communications

A Multi-Parameter Based Vertical Handover Decision Scheme for M2M Communications in HetMANET

A New Proposed Algorithm for the Priority of the Cellular Calls

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