We propose Otiy, a node-centric location service that limits the impact of location updates generate by mobile nodes in IEEE802.11-based wireless mesh networks. Existing location services use node identifiers to determine the locator (aka anchor) that is responsible for keeping track of a node's location. Such a strategy can be inefficient because: (i) identifiers give no clue on the node's mobility and (ii) locators can be far from the source destination shortest path, which increases both location delays and bandwidth consumption. To solve these issues, Otiy introduces a new strategy that identifies nodes to play the role of locators based on the likelihood of a destination to be close to these nodes- i.e., locators are identified depending on the mobility pattern of nodes. Otiy relies on the cyclic mobility patterns of nodes and creates a slotted agenda composed of a set of predicted locations, defined according to the past and present patterns of mobility. Correspondent nodes fetch this agenda only once and use it as a reference for identifying which locators are responsible for the node at different points in time. Over a period of about one year, the weekly proportion of nodes having at least 50 of exact location predictions is in average about 75 . This proportion increases by 10 when nodes also consider their closeness to the locator from only what they know about the network.
Mobile radio communications raise two major problems. First: a very poor radio link quality. Second: the users' mobility, which requires the management of their position, is resource consuming (especially radio bandwidth). This paper focuses on the second issue and proposes an intelligent method for users locating: the alternative strategy (AS). Our proposal is based on the observation that the mobility behavior of a majority of people can be foretold. If taken into consideration by the system, this characteristic can save signaling messages due to mobility management procedures, leading thus to savings in the system resources. Several versions of the AS are described: a basic version for long term events (i.e., received calls and registrations), and versions with increased memory for short and medium term events. The evaluation of the basic versions was performed using analytic and simulation approaches. It shows that storing the mobility related information brings great savings in system resources when the users have medium or high predictable mobility patterns. More generally speaking, this work points out the fact that the future systems will have to integrate users related information in order: firstly: to provide customized services and secondly: to save system resources. On the other hand, current trends in mobile communications show that adaptive and dynamic system capabilities require that more information to be collected and computed. >