In wireless mobile environments, data requests based on the location of mobile clients (MCs) have increased. The requested data, called location-dependent data (LDD), may be uncertain if MCs use terms of general distance like "near". Fuzzy theory allows us to represent uncertainty without sharp boundaries. In this paper we quantify the fuzziness and propose a method for constructing the data region of LDD by the degree of the distance between LDDs' and MCs' locations. In simulation studies, we evaluate the LDD regions (LDRs) in various situations: MCs' extensive and intensive queried pattern in data regions of two "near" senses and civilized regions with regional features. Our performance evaluation shows that the number of database accesses in proposed LDRs can be reduced in each case.

There are two principal aspects of "mobility" in location-aware computing: (1) how to support mobility and (2) how to exploit it. This paper considers the latter, while many existing works only concentrate on the former. This work is trying to prove that the performance of location-aware systems will be greatly improved by understanding the user's movement. In this paper, we propose a novel location update protocol called state-based location update protocol (SLUP), which significantly minimizes the energy consumption of mobile client by exploiting a syntactic information of a user's movement. This concept is called mobility-awareness which is a kind of context-awareness. Moreover, there are three variations of the proposed protocol in terms of how to choose the optimal state: SLUP/BS, SLUP/UITR, and SLUP/IUT. Experimental results show that the proposed protocol outperforms the well-known existing protocols such as dead-reckoning and distance-based protocol, and that the SLUP/IUT approach can achieve different performance tradeoffs between energy efficiency and location accuracy by fine-tuning its algorithmic parameter Tiut.

This letter proposes a group-based distributed air index (called GDI) using two-leveled groups by partitioning the identifiers of data items to reduce the size of the index. GDI provides both global and local views of data items and multiple pointers to data items in a single access to an index. Simulation results show that GDI outperforms the existing index in terms of multiple data access, energy conservation and data waiting time.

This paper presents a novel analytical approach to evaluate the signaling load of Mobile IPv6 (MIPv6) and Hierarchical Mobile IPv6 (HMIPv6). Previous analytical approaches for IP mobility management have not provided a complete and general framework for the performance analysis; no consideration of either periodic binding refresh cost or extra packet tunneling cost from the viewpoint of IP mobility management, and no in-depth investigation with respect to various system parameters. In this paper, according to the proposed analytical approach, we derive the location update costs (i.e., the sum of binding update costs and binding refresh costs), packet tunneling costs, inside-domain signaling costs, outside-domain signaling costs, and total signaling costs, which are generated by a mobile node (MN) during its average domain residence time in case MIPv6 or HMIPv6 is deployed under the same network architecture, respectively. Moreover, based on these derived costs, we evaluate the impacts of various system parameters on the signaling costs generated by an MN in MIPv6 and HMIPv6. The aim of this paper is not to determine which protocol performs better, but evaluate the performance that can be expected for each protocol under the various conditions, broaden our deep understanding of the various parameters that may influence the performance, and provide insight for the deployment of the two protocols.