MobiCom '96 Proceedings of the 2nd annual international conference on Mobile computing and networking
Prediction-Based Dynamic Load-Sharing Heuristics
IEEE Transactions on Parallel and Distributed Systems
Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
A structured channel borrowing scheme for dynamic load balancing in cellular networks
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
A performance study of a distributed algorithm for dynamic channel allocation
Proceedings of the 3rd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
An efficient approach for distributed channel allocation in cellular mobile networks
DIALM '01 Proceedings of the 5th international workshop on Discrete algorithms and methods for mobile computing and communications
A distributed algorithm for dynamic channel allocation
Mobile Networks and Applications - Analysis and Design of Multi-Service Wireless Networks
D-CAT: an efficient algorithm for distributed channel allocation in cellular mobile networks
Mobile Networks and Applications
Effects of hotspots on throughput in mobile ad hoc networks
PDCN'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: parallel and distributed computing and networks
Challenges of computing in mobile cellular environment-a survey
Computer Communications
Efficient distributed channel allocation for cellular networks
Computer Communications
| Hi-index | 0.00 |
We propose a dynamic load balancing scheme for the tele-traffic hot spot problem in cellular networks. A tele-traffic hot spot is a region of adjacent hot cells where the channel demand has exceeded a certain threshold. A hot spot is depicted as a stack of hexagonal `Rings' of cells and is classified as complete if all cells within it are hot. Otherwise it is termed incomplete. The rings containing all cold cells outside the hot spot are called `Peripheral Rings'. Our load balancing scheme migrates channels through a structured borrowing mechanism from the cold cells within the `Rings' or `Peripheral Rings' to the hot cells constituting the hot spot. A hot cell in `Ring i' can only borrow a certain fixed number of channels from adjacent cells in `Ring i+1'. We first propose a load balancing algorithm for a complete hot spot, which is then extended to the more general case of an incomplete hot spot. In the latter case, by further classifying a cell as cold safe, cold semi-safe or cold unsafe, a demand graph is constructed which describes the channel demand of each cell within the hot spot or its `Peripheral Rings' from its adjacent cells in the next outer ring. The channel borrowing algorithm works on the demand graph in a bottom up fashion, satisfying the demands of the cells in each subsequent inner ring until `Ring 0' is reached. A Markov chain model is first developed for a cell within a hot spot, the results of which are used to develop a similar model which captures the evolution of the entire hot spot region. Detailed simulation experiments are conducted to evaluate the performance of our load balancing scheme. Comparison with another well known load balancing strategy, known as CBWL, shows that under moderate and heavy tele-traffic conditions, a performance improvement as high as 12% in terms of call blockade is acheived by our load balancing scheme.