With the mobile devices becoming increasinglv popular, there is a new appetite for applicationsfor these devices. However. the problem faced by the application developers is that such devires have limited processing abilin together nirh limited memorr. At rhe same time. the servers have faster processing speed and larger memocv. In this case, an ohvious .solution uould have been to shifr majorin ofthe compuration and storage on to the server. Whenever a user wants 10 access 1hi.s i~for~imo~io~i. he generates a request and the results are traimsported to Itidher mobile device. The riser is required IO select various oprions at the device screen be/ore gerring the final resulr from the selyer. Each time an option is selected. dato tran.fer takes place between the tno ends.The handwidth availahle to a mobile user is inadequate to .facilitate such large and .frequent dato transfers. This paper presents a three-tier application model tliar w r k s specifica1l.v for the GSM networks fie. 7"' and higher &neration of'mobile networks). Using this model. varinii.i new and extremely u.seju1 applications can be de.sigwd. They would require no extra. expensive hardware and can easilyjit into the existing netnurk injrmtmcture.

Particle swarm optimization is a stochastic optimal search algorithm inspired by observing schools of fishes and flocks of birds. It is prevalent due to its easy implementation and fast convergence. However, PSO has been known to succumb to local optima when dealing with complex and higher dimensional optimization problems. To handle the problem of premutature convergence in PSO, this paper presents a novel adaptive inertia weight strategy and modifies the velocity update equation with the new Sbest term. To maintain the diversity of the population a particular radius r is introduced to impulse cluster particles. To validate the effectiveness of the proposed algorithm, various test functions and typical engineering applications are employed, and the experimental results show that with the changing of the proposed parameter the performance of PSO improves when dealing with these complex and high dimensional problems.