A dynamic load balancing strategy for channel assignment using selective borrowing in cellular mobile environment

  • Authors:

  • Sajal K. Das;Sanjoy K. Sen;Rajeev Jayaram

  • Affiliations:

  • Center for Research in Wireless Computing, Department of Computer Sciences, University of North Texas, P.O. Box 311366, Denton, TX;Center for Research in Wireless Computing, Department of Computer Sciences, University of North Texas, P.O. Box 311366, Denton, TX;Center for Research in Wireless Computing, Department of Computer Sciences, University of North Texas, P.O. Box 311366, Denton, TX

  • Venue:
  • Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
  • Year:
  • 1997

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Abstract

We propose a dynamic load balancing scheme for the channel assignment problem in a cellular mobile environment. As an underlying approach, we start with a fixed assignment scheme where each cell is initially allocated a set of channels, each to be assigned on demand to a user in the cell. A cell is classified as ‘hot’, if the degree of coldness of a cell (defined as the ratio of the number of available channels to the total number of channels for that cell), is less than or equal to some threshold value. Otherwise the cell is `cold'. Our load balancing scheme proposes to migrate unused channels from underloaded cells to an overloaded one. This is achieved through borrowing a fixed number of channels from cold cells to a hot one according to a channel borrowing algorithm. A channel assignment strategy is also proposed based on dividing the users in a cell into three broad types—‘new’, ‘departing’, ‘others’—and forming different priority classes of channel demands from these three types of users. Assignment of the local and borrowed channels are performed according to the priority classes. Next, a Markov model for an individual cell is developed, where the state is determined by the number of occupied channels in the cell. The probability for a cell being hot and the call blocking probability in a hot cell are derived, and a method to estimate the value of the threshold is also given. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. The performance of our load balancing scheme is compared with the fixed channel assignment, simple borrowing, and two existing strategies with load balancing (e.g., directed retry and CBWL), and a significant improvement of the system behavior is noted in all cases.