Optimal Location Management Research Articles

Optimal location management in LTE networks using evolutionary techniques

SummaryWireless network is considered a vital enabler in the world of information technology, specifically, LTE and LTE advanced networks, which are the latest technologies owing to their fast speed, robustness, and large bandwidth. However, in spite of the aforementioned advancements, signaling overhead poses critical challenges in terms of network availability, especially those caused by location management messages which are related to users’ mobility behavior. This paper seeks to address the problem of signaling overhead caused by the location management messages specifically, tracking area update (TAU) and paging by deploying three evolutionary algorithms, namely particle swarm optimization (PSO), artificial bee colony (ABC), and gravitational search algorithm (GSA). The deployed algorithms guarantee yielding the minimum values of the signaling overhead for TAU, paging, and the battery power consumption of the user. It is shown that ABC‐based algorithm has faster convergence and better signaling overhead when compared with other implemented algorithms. Moreover, the measured relative standard deviation (RSD) value of all algorithms shows low uncertainty of around 1% for the objective function and 3% for the paging, TAU, and power. Hence, the three applied optimization algorithms have proven to be efficient and reliable for solving the problem in a large‐scale environment.

Location management in LTE networks using multi-objective particle swarm optimization

Long-term evolution (LTE) and LTE-advance (LTE-A) are widely used efficient network technologies serving billions of users, since they are featured with high spectrum efficiency, less latency, and higher bandwidth. Despite remarkable advantages offered by these technologies, signaling overhead remains a major issue in accessing the network. In particular, the load of signaling is mainly attributed to location management. This paper proposes an efficient approach for minimizing the total signaling overhead of location management in LTE networks using multi-objective particle swarm optimization (MOPSO). Tracking area update (TAU) and paging are considered to be the main elements of the signaling overhead of optimal location management in LTE. In addition, the total inter-list handover contributes significantly to the total signaling overhead. However, the total signaling cost of TAU and paging is adversely related to the total inter-list handover. Hence, two cost functions should be minimized where the first function is the total signaling cost of TAU and paging and the second cost function is the total signaling overhead. The trade-off between these two objectives can be circumvented by MOPSO, which alleviates the total signaling overhead. A set of non-dominated solutions on the Pareto-optimal front is defined and the best compromise solution is presented. The efficacy and the robustness of the proposed algorithm have been proven through a large scale environment problem illustrative example. The location management in LTE networks using MOPSO best compromise solution has been compared to the results obtained by a mixed integer non-linear programming (MINLP) algorithm.

Location management for GPRS

In cellular wireless networks, location management is an important mechanism that enables network to discover the current attachment point of a mobile so as to facilitate successful information delivery. Although the design of optimal location management has been studied extensively for GSM, it is surprising that little, or possibly no, attention has been given to the consideration of location management design for General Packet Radio Service (GPRS), given that it is fast becoming a de facto system. Unlike GSM, the tracking of mobiles (MS) in the GPRS is made through routing area (RA) and location area (LA). For the first time, the mode of operation of MS, mobility management of MS and the network operation mode are considered as part of the proposed location management design model. The objective of the paper is to study in detail the impacts of the various varying parameters have on the performance of location management in GPRS. Two schemes, namely, greedy algorithm and optimal algorithm, are proposed and the mathematical models are developed in this paper. Comparative studies of the two schemes are carried out and discussed.

Optimal location management for two-tier PCS networks

One of the most important issues in Personal Communication Service (PCS) networks is location management, which keeps track of the Mobile Terminals (MTs) moving from place to place. In this paper, we analytically derive cost functions of location updates and paging for a dynamic movement-based location management scheme for PCS networks with two-tier mobility databases. We prove analytically that there is a unique optimal movement threshold that minimizes the total cost of Home Location Register location updates, Visitor Location Register location updates, and paging, per call arrival. An effective algorithm is proposed to find the optimal movement threshold. Furthermore, we propose a hybrid location management scheme, in which when the call-to-mobility ratio is larger than a threshold, the optimal dynamic movement-based scheme is adopted. Otherwise, the static location update is adopted. The Newton approximation method is adopted to find this threshold. Our study shows that the proposed hybrid scheme outperforms both the dynamic movement-based scheme and the static location update scheme.

Location management for database migration in ATM networks

Since in broadband networks the whole contents of a database can be transferred from one site to another in a short period, database migration is expected to be one of the most powerful database operations in future distributed database systems. In an environment with database migration, it is necessary to develop a method to manage the location of each database so as to allow accessing of migrating databases. In this paper, we first propose several database location management methods, some of which make use of the features of ATM (Asynchronous Transfer Mode) networks. Then, we compare the performance of these methods by simulation study for various system parameters, such as the frequency of queries and of database migration, and the scale of the network. The results are used to identify the optimal location management method for a given system environment.