Community healthcare mesh network engineering in white space frequencies

The transition from analog to digital television has availed new spectrum called white space, which can be used to boost the capacity of wireless networks on an opportunistic basis. One sector in which there is a need to use white space frequencies is the healthcare secto

Service Provisioning for Lightweight Community Cloud Infrastructures

Service provision in low power network environments remains a very difficult task due to the lightweight nature of the devices involved. This paper explores and demonstrates the efficacy of the light weight resource allocation protocol (LRAP) in allocating services in a heterogeneous network environment consisting of primarily low power nodes. We show that with the correct resource brokering approach, services can be provisioned on nodes in a way which does not cripple individual nodes in network, while ensuring that services are distributed to nodes in the network where the lowest impact on overall performance will be made. This strategy provides an effective way of providing services especially in low power environment

Cooperative Behaviours with Swarm Intelligence in Multirobot Systems for Safety Inspections in Underground Terrains

Underground mining operations are carried out in hazardous environments. To prevent disasters from occurring, as often as they do in underground mines, and to prevent safety routine checkers from disasters during safety inspection checks, multirobots are suggested to do the job of safety inspection rather than human beings and single robots. Multirobots are preferred because the inspection task will be done in the minimum amount of time. This paper proposes a cooperative behaviour for a multirobot system (MRS) to achieve a preentry safety inspection in underground terrains. A hybrid QLACS swarm intelligent model based on Q-Learning (QL) and the Ant Colony System (ACS) was proposed to achieve this cooperative behaviour in MRS. The intelligent model was developed by harnessing the strengths of both QL and ACS algorithms. The ACS optimizes the routes used for each robot while the QL algorithm enhances the cooperation between the autonomous robots. A description of a communicating variation within the QLACS model for cooperative behavioural purposes is presented. The performance of the algorithms in terms of without communication, with communication, computation time, path costs, and the number of robots used was evaluated by using a simulation approach. Simulation results show achieved cooperative behaviour between robots

ITIKI: bridge between African indigenous knowledge and modern science of drought prediction

Droughts are the most common type of natural disaster in Africa and the problem is compounded by their complexity. The agriculture sector still forms the backbone of most economies in Africa, with 70% of output being derived from rain-fed smallscale farming; this sector is the first casualty of droughts. Accurate, timely and relevant drought predication information enables a community to anticipate and prepare for droughts and hence minimize the negative impacts. Current weather forecasts are still alien to African farmers, most of whom live in rural areas and struggle with illiteracy and poor communications infrastructure. However, these farmers hold indigenous knowledge not only on how to predict droughts, but also on unique coping strategies. Adoption of wireless sensor networks and mobile phones to provide a bridge between scientific and indigenous knowledge of weather forecasting methods is one way of ensuring that the content of forecasts and the dissemination formats meet local needs. A framework for achieving this integration is presented in this paper. A system prototype to implement this framework is also presented

Network Selection for Mobile Nodes in Heterogeneous Wireless Networks using Knapsack Problem Dynamic Algorithms

With the accelerated proliferation wireless networks ranging from GPRS and EDGE to high speed networks such as HSPDA and Mobile Wi-Fi, network selection by mobile nodes will benefit more from knowledge of Network Capability of candidate networks. Network selection is important for handover in heterogeneous wireless environment. User Profiles/Needs and Network Capability will greatly influence the next logical step after network discovery, which is Network Selection. We examine the Dynamic Network Selection paradigm that uses User Profiling/needs to rank networks for selection and ignore networks with less capacity than required, using the Knapsack problem 0/1 Dynamic algorithm and the Knapsack problem Optimization Algorithm

Framework for Predicting Droughts in Developing Countries Using Sensor Networks and Mobile Phones

Drought is the most complex and least understood of all natural disasters and it affects more people than any other hazard. Droughts have become synonymous with the developing countries and in particular the Sub-Saharan Africa where the hazard is chronic. Effects of droughts can be mitigated if accurate and timely drought predications were to be done. Unfortunately, despite the enormous advancements in science, predictions only provide indications of trends. A major weakness of the existing tools is the emphasis on macro/international level information. The tools also tend to ignore the at risk community who happen to be host to very crucial traditional knowledge on droughts. In this paper, we propose an integrated drought predication framework that considers both scientific and traditional knowledge and combines the use of mobile phones with wireless sensor networks to be able to capture and relay micro drought parameters. The framework is an enhancement of ITU’s Ubiquitous Sensor Network (USN) Layers. In order to accommodate the diverse roles mobile phones play in our framework, Layer 2 (USN Access Networking) is implemented using three sub-layers composed of heterogeneous gateways