Elsevier

Computer Networks

Volume 55, Issue 5, 1 April 2011, Pages 1114-1131
Computer Networks

Optimized traffic flow assignment in multi-homed, multi-radio mobile hosts

https://doi.org/10.1016/j.comnet.2010.11.003Get rights and content

Abstract

Multi-radio mobile communication devices are increasingly gaining market share due to the diversity of currently deployed and continuously emerging radio access technologies. Multi-homing support in multi-radio terminals, i.e., simultaneous use of two or more radio interfaces, provides improved user experience through increase in available bandwidth capacity and reliability of wireless access. Furthermore, optimized assignment of application traffic flows to available interfaces and radio access bearer services contributes to economic and power consumption efficiency. We study the problem of traffic flow assignment in a mobile node, multi-homed through a set of different technology radio interfaces. We provide an analytical formulation for the problem and prove its hardness through transformation from the Multiple Knapsack Problem with Assignment Restrictions. Problem solutions are approximated with a heuristic algorithm that is based on local search and is characterized by efficient execution times for a wide set of realistic problem sizes. The quality of approximation is rather satisfactory and is evaluated through comparison of heuristic and exact solutions for a large set of randomly generated problem instances. Moreover, an evaluation of the approach through simulation supports these findings and provides an estimation of the associated mobility management overhead that is limited and allows real deployment of the decision mechanism.

Introduction

Wireless internet access is continuously expanding its geographical reach through a variety of radio access technologies (RATs). However, no single RAT may completely satisfy the bandwidth and QoS requirements set by current and emerging multimedia applications. Moreover, each RAT focuses on different degrees of user mobility in terms of speed and range. In order to benefit from radio access diversity, many modern mobile communication devices are multi-mode, i.e., they are equipped with multiple radio interfaces (3GPP, 802.11a/b/g/n, etc.). Moreover, special purpose mobile devices are emerging that provide aggregated bandwidth capacity to mobile business or vehicular users, through multiple wireless broadband subscriptions [1].

A multi-mode terminal (MMT) that is multi-homed has at least two global IP addresses, associated with respective radio interfaces. The IETF MONAMI6 WG has identified the benefits that mobile host multi-homing offers to both end users and network operators [2] and its successor, IETF MEXT WG, is working towards enhancing MIPv6 with multi-homing support. This capability will be enabled by allowing the registration of multiple Care-of Addresses (CoAs) with a certain Home Address [3]. Moreover, this specification is being complemented with support for binding flows to specific CoAs [4], allowing, thus, the execution of handoffs at a traffic flow level.

Given these enhancements to a basic mobility management protocol such as MIPv6, a mobile MMT extends its degrees of freedom for adapting its connectivity status to the changing traffic requirements and wireless networking context. For instance, the range of options for responding to the arrival of a traffic flow, when spare capacity in active radio interfaces is not available, may include: (a) activation of an inactive radio interface and its attachment to an appropriate radio bearer service, (b) horizontal handoff on an active radio interface towards a higher capacity bearer service, (c) redirection of one or more traffic flows, already served by one interface, to another interface for best utilization of available bandwidth capacity, etc. The set of available options on each occasion depends on the wireless context and the MMT’s traffic load and hardware configuration. Moreover, each alternative may have different impact on the fulfillment of user preferences and especially on economic efficiency and energy autonomy. Thus, evaluation and determination of the optimal operational state requires advanced and fast executing decision algorithms. Execution efficiency is required due to the frequently occurring triggers for decision making that include changes in served traffic, network conditions and device status (e.g. battery lifetime).

This work focuses on joint management of traffic, wireless connectivity and power consumption in the context of a multi-homed MMT operating in a dynamic environment. The MMT may have the role of an end-host serving its own traffic or the role of a mobile router that acts as an internet gateway to a personal area or vehicular network. We study the problem of assignment of application traffic flows (either inbound or outbound) to appropriate radio interfaces and radio bearer services in a way that: (a) satisfies the traffic flows’ QoS requirements and the bearer services’ capacity constraints, and (b) establishes the best tradeoff between economic cost and power consumption. For brevity reasons, the problem will be referred to as Traffic Flow Assignment Problem (TFAP). The economic cost factor of TFAP corresponds to network usage cost, while power consumption is due to the operation of active radio interfaces. Due to the dynamic nature of problem parameters the MMT iteratively faces TFAP instances of variable size during its operation lifetime.

We provide an analytical formulation for the TFAP that maps the problem to a bi-objective combinatorial optimization problem. The formulation takes into account additional constraints, as compared to prior work, that contribute to a more realistic representation of the problem domain. The bi-objective problem is solved by setting one of the objectives as a target for minimization (economic cost) and the other objective (power consumption) as an additional problem constraint by appropriately choosing an upper limit for its allowed values. We study the complexity of the TFAP and prove its hardness through transformation from the Multiple Knapsack Problem with Assignment Restrictions that is NP-Hard [5]. Given the complexity of TFAP and requirements for frequent and fast execution, we introduce a heuristic approximation algorithm that is based on local search and establishes a good balance between solution quality and execution time. A basic feature of the proposed algorithm is the combined use of two objective functions that guide the search towards minimum cost solutions with an upper limit on power consumption. Solution quality is evaluated by comparing heuristic and exact solutions for a large number of randomly generated problem instances. Moreover, the approach is evaluated with a discrete event simulator in order to study its merits over the time domain and the incurred mobility management overhead.

The rest of the paper is organized as follows: Section 2 presents relevant literature and makes a qualitative comparison of this work against it. Section 3 introduces an analytical formulation for the TFAP along with a study of its complexity. Moreover, it specifies the method that we have applied for its solution. A heuristic algorithm for the TFAP is presented in Section 4, while an extensive evaluation of its results and runtime performance is given in Section 5. Finally, the paper is concluded in Section 6 with open issues and possible extensions for future research.

Section snippets

Related work

Multi-homing is often employed by stub networks (enterprizes or Internet Service Providers – ISPs) in order to enhance the reliability, performance or independence (avoiding lock-in to a single provider) of their internet connectivity. Techniques and challenges related to the realization of multi-homing in IPv4 networks are summarized in [6]. Effective usage of a stub network’s links with its ISPs is a complementary issue to multi-homing deployment and involves distributing incoming and

Problem formulation

Assume a mobile multi-mode terminal (MMT) that is equipped with a set of different technology radio interfaces, e.g., 3GPP, IEEE 802.11x, WiMAX, etc. Let R={ri:1im,mN}, be the MMT’s available radio interfaces. Moreover, the MMT has multi-homing support, i.e., it is capable of simultaneously using two or more of its radio interfaces for serving its data traffic.

The MMT’s current location lies in the overlapping service areas of a set of radio access networks (RANs). The RANs correspond to

A heuristic algorithm for the TFAP

In this section we introduce a heuristic algorithm for approximating the solution of a TFAP instance. The algorithm, that is based on local search, starts from initial problem solutions and gradually modifies them towards a better approximation of the actual solution. Initial problem solutions are obtained through heuristic construction algorithms. These algorithms “construct” a valid traffic flow assignment S by assigning flows one-by-one to appropriate radio interfaces with a first-fit

Experimental setting

The evaluation of the local search algorithm for the TFAP is based on the comparison of heuristic and exact solutions for a large number of randomly generated problem instances. Heuristic solutions are produced from a Java implementation of the proposed algorithm for the TFAP, while exact solutions result from a tool capable of solving Integer Linear Programming problems [31] that will be henceforth referred to as ILP solver. The random generation of problem instances is based on three problem

Conclusions and future work

We have studied the problem of traffic flow assignment in a mobile node, multi-homed through a set of different technology radio interfaces. The problem involves association of a subset of available radio interfaces with appropriate radio bearer services and assignment of application traffic flows to them, in a way that economic cost is minimized and power consumption does not exceed a predefined limit. We have provided an analytical formulation for the problem and described its relationship

Acknowledgements

The authors thank the anonymous reviewers for their constructive comments that contributed to the improvement of the extent and quality of this work. Special thanks need to be attributed to Lecturer Evangelos Markakis for the useful discussions we had on the proof of the Traffic Flow Assignment Problem’s complexity.

Vassilis E. Zafeiris is Ph.D. researcher in the Informatics Department of the Athens University of Economics and Business. He received his Dipl. in Electrical Engineering from the National Technical University of Athens (NTUA) in 2001 and a M.Sc. in Information Systems from the Athens University of Economics and Business in 2003. His research interests include mobility management in next generation networks, handover management in heterogeneous radio access networks, software agents and their

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    Vassilis E. Zafeiris is Ph.D. researcher in the Informatics Department of the Athens University of Economics and Business. He received his Dipl. in Electrical Engineering from the National Technical University of Athens (NTUA) in 2001 and a M.Sc. in Information Systems from the Athens University of Economics and Business in 2003. His research interests include mobility management in next generation networks, handover management in heterogeneous radio access networks, software agents and their application in mobile networking.

    Emmanouel A. Giakoumakis is an associate professor of Software Engineering in the Informatics Department of the Athens University of Economics and Business. He received his Dipl. in Electrical Engineering and Ph.D. in Computer Engineering from the National Technical University of Athens (NTUA) in 1981 and 1988 respectively. He has served as President of the Hellenic Regulatory Authority for Telecommunications (2000–2005). His research interests include software engineering, software architectures and interoperability, biomedical applications and regulation and competition in electronic services.

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