Research Article Achieving Fair Spectrum Allocation and Reduced Spectrum Handoff in Wireless Sensor Networks: Modeling via Biobjective Optimization Sang-Seon Byun, 1 Kimmo Kansanen, 2 Ilangko Balasingham, 3 and Joon-Min Gil 4 1 Department of Computer Engineering, Catholic University of Pusan, Busan, Republic of Korea 2 Department of Electronics and Telecommunications, Norwegian University of Science and Technology, Trondheim, Norway 3 Rikshospitalet, Oslo University Hospital, Oslo, Norway 4 School of Information Technology Engineering, Catholic University of Daegu, Gyeongsan, Gyeongbuk, Republic of Korea Correspondence should be addressed to Joon-Min Gil; jmgil@cu.ac.kr Received 26 June 2014; Accepted 12 August 2014; Published 3 September 2014 Academic Editor: James J. Park Copyright © 2014 Sang-Seon Byun et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. his paper considers the problem of centralized spectrum allocations in wireless sensor networks towards the following goals: (1) maximizing fairness, (2) relecting the priority among sensor data, and (3) avoiding unnecessary spectrum handof. We cast this problem into a multiobjective mixed integer nonconvex nonlinear programming that is deinitely diicult to solve at least globally without any aid of conversion or approximation. To tackle this intractability, we irst convexify the original problem using arithmetic-geometric mean approximation and logarithmic change of the decision variables and then deploy weighted Chebyshev norm-based scalarization method in order to collapse the multiobjective problem into a single objective one. Finally, we apply simple rounding method in order to obtain approximate integer solutions. he results obtained from the numerical experiments show that, by adjusting the weight on each objective function, the proposed algorithm allocates spectrum bands fairly with well observing each sensor’s priority and reduced spectrum handofs. 1. Introduction he demand of allocating and using the radio frequency spectra is rapidly growing due to increasing number of wireless and mobile communication applications, where the industry has reached the limits of current static spectrum allocation. However, actual measurements illustrate that the scarcity is not a result of heavy usage of the spectrum. It is merely due to the ineiciency of the static spectrum allocation pursued by regulators [1]. Dynamic spectrum allocation may resolve this paradox by opening assigned, but sparsely used, spectrum resources to secondary users [2–4]. It exploits underutilized spectrum resources along time or frequency dimension and provides eicient and intensive dynamic spectrum access through the detection of spectrum opportunity and adaptive modulation. Such dynamic spectrum access schemes can be consid- ered in wireless sensor networks (WSNs) as well. Typical WSNs are composed of resource-constrained sensors respon- sible for monitoring physical phenomena and reporting to sink points. One of the primary objectives of WSNs is to transmit monitored results timely and concurrently, without using large amount of network resources. he dynamic spectrum access becomes very vital to achieve such timely and concurrent transmissions in WSNs; for instance, in a WSN for real time surveillance system [5, 6] or real time machine-to-machine communications [7], the transmissions of video or image data captured by the sensors require high bandwidth and multiple spectra [8]. Subsequently, the following major principles can be made. 1.1. Fair Allocation of Idle Spectrum Bands. If too many sensors attempt to transmit their data simultaneously, current idle spectrum resources may be insuicient to support all transmissions. In this situation, scarce spectrum resources Hindawi Publishing Corporation Modelling and Simulation in Engineering Volume 2014, Article ID 406462, 12 pages http://dx.doi.org/10.1155/2014/406462