278 research outputs found
Applications of Soft Computing in Mobile and Wireless Communications
Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
Seamless Vertical Handoff using Invasive Weed Optimization (IWO) algorithm for heterogeneous wireless networks
AbstractHeterogeneous wireless networks are an integration of two different networks. For better performance, connections are to be exchanged among the different networks using seamless Vertical Handoff. The evolutionary algorithm of invasive weed optimization algorithm popularly known as the IWO has been used in this paper, to solve the Vertical Handoff (VHO) and Horizontal Handoff (HHO) problems. This integer coded algorithm is based on the colonizing behavior of weed plants and has been developed to optimize the system load and reduce the battery power consumption of the Mobile Node (MN). Constraints such as Receiver Signal Strength (RSS), battery lifetime, mobility, load and so on are taken into account. Individual as well as a combination of a number of factors are considered during decision process to make it more effective. This paper brings out the novel method of IWO algorithm for decision making during Vertical Handoff. Therefore the proposed VHO decision making algorithm is compared with the existing SSF and OPTG methods
Delay Minimizing User Association in Cellular Networks via Hierarchically Well-Separated Trees
We study downlink delay minimization within the context of cellular user
association policies that map mobile users to base stations. We note the delay
minimum user association problem fits within a broader class of network utility
maximization and can be posed as a non-convex quadratic program. This
non-convexity motivates a split quadratic objective function that captures the
original problem's inherent tradeoff: association with a station that provides
the highest signal-to-interference-plus-noise ratio (SINR) vs. a station that
is least congested. We find the split-term formulation is amenable to
linearization by embedding the base stations in a hierarchically well-separated
tree (HST), which offers a linear approximation with constant distortion. We
provide a numerical comparison of several problem formulations and find that
with appropriate optimization parameter selection, the quadratic reformulation
produces association policies with sum delays that are close to that of the
original network utility maximization. We also comment on the more difficult
problem when idle base stations (those without associated users) are
deactivated.Comment: 6 pages, 5 figures. Submitted on 2013-10-03 to the 2015 IEEE
International Conference on Communications (ICC). Accepted on 2015-01-09 to
the 2015 IEEE International Conference on Communications (ICC
Cooperation Between Stations in Wireless Networks
In a wireless network, mobile nodes (MNs) repeatedly perform tasks such as layer 2 (L2) handoff, layer 3 (L3) handoff and authentication. These tasks are critical, particularly for real-time applications such as VoIP. We propose a novel approach, namely Cooperative Roaming (CR), in which MNs can collaborate with each other and share useful information about the network in which they move. We show how we can achieve seamless L2 and L3 handoffs regardless of the authentication mechanism used and without any changes to either the infrastructure or the protocol. In particular, we provide a working implementation of CR and show how, with CR, MNs can achieve a total L2+L3 handoff time of less than 16 ms in an open network and of about 21 ms in an IEEE 802.11i network. We consider behaviors typical of IEEE 802.11 networks, although many of the concepts and problems addressed here apply to any kind of mobile network
An Adaptive Multimedia-Oriented Handoff Scheme for IEEE 802.11 WLANs
Previous studies have shown that the actual handoff schemes employed in the
IEEE 802.11 Wireless LANs (WLANs) do not meet the strict delay constraints
placed by many multimedia applications like Voice over IP. Both the active and
the passive supported scan modes in the standard handoff procedure have
important delay that affects the Quality of Service (QoS) required by the
real-time communications over 802.11 networks. In addition, the problem is
further compounded by the fact that limited coverage areas of Access Points
(APs) occupied in 802.11 infrastructure WLANs create frequent handoffs. We
propose a new optimized and fast handoff scheme that decrease both handoff
latency and occurrence by performing a seamless prevent scan process and an
effective next-AP selection. Through simulations and performance evaluation, we
show the effectiveness of the new adaptive handoff that reduces the process
latency and adds new context-based parameters. The Results illustrate a QoS
delay-respect required by applications and an optimized AP-choice that
eliminates handoff events that are not beneficial.Comment: 20 pages, 14 figures, 4 table
An integrated priority-based cell attenuation model for dynamic cell sizing
A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual
community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules
through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA
module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. Real-time predicted mobile traffic from the EFuNN structure was used to control the size of all the cells.Results obtained demonstrate the robustness of the integrated module in recognizing the temporal pattern of the mobile traffic and dynamically controlling the cell size in order to reduce the number of calls dropped
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