A survey of identity and handoff management approaches for the future Internet

Tuncer, Hasan; Mishra, Sumita; Shenoy, Nirmala

doi:10.1016/j.comcom.2012.07.017

Cited by 21 publications

(15 citation statements)

References 46 publications

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“…The proof begins with the remark that the handoff state machine splits the scenario length according to (13). This equation is Both (15) and (16) show a correlation between rTiB and rEHO (along with other factors).…”

Section: Proposition (Correlation and Causation) The Random Variablementioning

confidence: 99%

“…It is the relationship between users and providers, which is many-to-many. Finally, communicating entities in the Future Internet must have the ability to be identifiable [13]. That is, there must be a unique identifier associated with each producer or consumer of information [14].…”

Section: Definition (Relations Users-terminals-poas) Let U M and Amentioning

confidence: 99%

“…deterministic. Observe that(13) holds for any handoff scenario, where (DISCO) = DTiD, (CONN) is dwelling time in connection, (PREP) is dwelling time in preparation, (EXEC) = CHoL, and (EVAL) is dwelling time in evaluation. TST = (DISCO) + (CONN) + (PREP) + (EXEC) + (EVAL).…”

mentioning

confidence: 99%

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Multipurpose mobility services for the Future Internet

Gonzalez-Horta¹,

Mejía-Álvarez

Buenfil-Alpuche

2015

Computer Networks

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Mobility and handoff management is a key problem of the Future Internet. Current solutions provide mobility services, such as seamless mobility, adaptive mobility, alwaysbest-connected (ABC) mobility, etc. The problem is these services work separately and ignore conflicts between them. This may lead to improve one service and degrade others. Hence, we propose multipurpose mobility as a new holistic service that integrates multiple mobility services and supplies a fair balance between all the objectives to meet. As a proofof-concept, we integrate the seamless, ABC, and adaptive mobility services, which have objectives in conflict. We formulate a Multi-Objective Handoff Optimization Problem, which grades as NP-Hard. We develop a heuristic handoff algorithm, which provides nearoptimal and balanced solutions. Finally, we evaluate the algorithm through random samples of simulated handoff scenarios, which provide hit rates over 90%.

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Section: Proposition (Correlation and Causation) The Random Variablementioning

confidence: 99%

Section: Definition (Relations Users-terminals-poas) Let U M and Amentioning

confidence: 99%

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Multipurpose mobility services for the Future Internet

Gonzalez-Horta¹,

Mejía-Álvarez

Buenfil-Alpuche

2015

Computer Networks

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“…The BS can be perceived as an antenna which provides a wireless interface to the mobile users within the location area (LA). The LA is defined as a set of "cells" constituting a small geographical area which is a part of a service provider's service zone [10,16].…”

Section: Introductionmentioning

confidence: 99%

Bee system-based energy efficient base station operation in mobile cellular networks

Biswash

Sarkar

Nagaraj

2015

2015 International Conference on Computing, Networking and Communications (ICNC)

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Ubiquitous communication is being envisioned as the daunting feature in the next generation of cellular networks. However, it comes with the price tag of humungous energy consumption, a significant fraction of which is due to the base stations within a service area. In this paper, we propose a cooperation technique among base stations in a cellular network that reduces their energy consumption. Our algorithm is based on nature-inspired computing, especially the bee system. In our proposed algorithm, all base stations within a given area work together to provide a better quality of experience (QoE) to a mobile user. A base station first checks for availability of unutilized (or underutilized) bandwidth. If the availability is over a certain threshold, all base stations will perform a reunion procedure to provide a uniform distribution of the consumed bandwidth (bandwidth load), thereby providing better service to users. We have also formulated a novel analysis technique to determine the effectiveness, efficiency and scalability of the proposed scheme. Our results show-case the fact that our algorithm indeed yields higher energy efficiency at the base stations when compared to traditional schemes.

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“…So, either in the form of Call Detail Records (CDRs) or with specialized apps [22], [25], people's mobility data can be collected from mobile phones. Therefore, in the recent years, researchers have devoted considerable effort to collecting and studying human mobility patterns [7] and have applied their understanding to a variety of critical problems ranging from disease spreading [2], urban planning, smart and green transportation to network infrastructure [37,14], economy and marketing [30], and mobile network services [13]. Nonetheless, despite the advances in communications technologies and other important achievements, human mobility still represents an open and challenging research issue.…”

Section: Introductionmentioning

confidence: 99%

On the properties of human mobility

Papandrea

Jahromi

Zignani

et al. 2016

Computer Communications

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The current age of increased people mobility calls for a better understanding of how people move: how many places does an individual commonly visit, what are the semantics of these places, and how do people get from one place to another. We show that the number of places visited by each person (Points of Interest -PoIs) is regulated by some properties that are statistically similar among individuals. Subsequently, we present a PoIs classification in terms of their relevance on a per-user basis. In addition to the PoIs relevance, we also investigate the variables that describe the travel rules among PoIs in particular, the spatial and temporal distance. As regards the latter, existing works on mobility are mainly based on spatial distance. Here we argue, rather, that for human mobility the temporal distance and the PoIs relevance are the major driving factors. Moreover, we study the semantic of PoIs. This is useful for deriving statistics on people's habits without breaking their privacy. With the support of different datasets, our paper provides an in-depth analysis of PoIs distribution and semantics; it also shows that our results hold independently of the nature of the dataset in use. We illustrate that our approach is able to effectively extract a rich set of features describing human mobility and we argue that this can be seminal to novel mobility research.

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A survey of identity and handoff management approaches for the future Internet

Cited by 21 publications

References 46 publications

Multipurpose mobility services for the Future Internet

Multipurpose mobility services for the Future Internet

Bee system-based energy efficient base station operation in mobile cellular networks

On the properties of human mobility

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