Machine learning algorithms for wireless sensor networks: A survey

This paper presents a novel algorithm to rapidly create a high quality network plan for IEEE 802.11 based WLAN according to assigned design requirements. The algorithm uses a Genetic Algorithm (GA) to explore the design space, and a IEEE 802.11 rate adaptation aware QoS estimation functionality to provide feedback for the algorithm and for a network designer. The algorithm selects AP devices, locations, antennas, as well as AP configuration including transmission power and frequency channel. The algorithm was used in WLAN planning for a suburb, which is under development in Tampere-Lempaala area in Finland. Compared to manual network planning, the developed algorithm was able to create a network plan with 133 % capacity, 98 % coverage, and 93 % cost. Manually the corresponding network planning took hours, whereas the algorithm computation time was 15 minutes.

Genetic Algorithm to Optimize Node Placement and Configuration for WLAN Planning

Mobile health has been receiving a lot of attention from patients, healthcare professionals, application developers, network service providers and researchers. Mobile health is more than just some healthcare applications on a mobile phone and it can involve sensors and wireless networks in monitoring various conditions, mobile devices to access numerous healthcare services, healthcare professionals to make decisions and provide emergency care, and for the elderly to manage their daily activities in independent living. More specifically, m-health can result in major advances in (a) expanding healthcare coverage, (b) improving decision making, (c) managing chronic conditions and (d) providing suitable healthcare in emergencies. To help realize these advances, there are major research challenges that need to be addressed. We classify these challenges in four categories of (a) patients related, (b) healthcare professionals related, (c) IT related and (d) applications related challenges. Within each category, we identify several research problems, and we present some high-level and preliminary solutions along with an agenda for future research. The paper may provide a platform for future research and decision-making related to patients, healthcare professionals, applications, and infrastructure. These decisions will significantly impact how future mobile health services will be designed, developed, evaluated, and adopted globally. We present an integrated view of mobile health.Mobile health can lead to many significant improvements in healthcare.There are many important challenges in mobile health.We classify mobile health challenges in four categories.For each category, the challenges and possible solutions are discussed.

Mobile health

Quality of service (QoS) routing is one of the critical challenges in wireless sensor networks (WSNs), especially for surveillance systems. Multihop data transmission of WSNs, due to the high packet loss and energy-efficiency, requires reliable links for end-to-end data delivery. Current multipath routing works can provision QoS requirements like end-to-end reliability and delay, but suffer from a significant energy cost. To improve the efficiency of the network with multiconstraints QoS parameters, in this paper we model the problem as a multiconstrained optimal path problem and propose a distributed learning automaton (DLA) based algorithm to preserve it. The proposed approach leverages the advantage of DLA to find the smallest number of nodes to preserve the desired QoS requirements. It takes several QoS routing constraints like end-to-end reliability and delay into account in path selection. We simulate the proposed algorithm, and the obtained results verify the effectiveness of our solution. The results demonstrate that our algorithm has a better performance than current state-of-the-art competitive algorithms in terms of end-to-end delay and energy-efficiency.

Energy-Efficient Algorithm for Reliable Routing of Wireless Sensor Networks

A power efficient cluster-based routing algorithm for wireless sensor networks

Many researchers employ IEEE802.15.4 as communication technology for wireless sensor networks (WSNs). However, medium access control (MAC) layer requirements for communications in wireless sensor networks (WSNs) vary because the network is usually optimized for specific applications. Thus, one particular standard will hardly be suitable for every possible application. Two general categories of MAC techniques exist: contention based and schedule based. This paper explains these two main approaches and includes examples of each one. The paper concludes with a unique performance analysis and comparison of benefits and limitations of each protocol with respect to WSNs.

https://journals.sagepub.com/doi/pdf/10.1155/2012/834784

MAC Protocols Used by Wireless Sensor Networks and a General Method of Performance Evaluation

An important issue in the widespread deployment of infrastructure based wireless local area networks (WLANs) is the network design. In this paper, we propose a new WLAN design approach that focuses on assuring sufficient data rate capacity to meet expected user demand in the coverage area, while still satisfying signal coverage and interference level requirements. Noting the low cost of WLAN access points, we formulate a novel mathematical network design model within the framework of constraint satisfaction problems. Our model is termed the capacity based WLAN constraint satisfaction problem (Cap-WLAN CSP). The solution of the Cap-WLAN CSP model yields a network design based on data rate demand by providing the access point locations, the frequency channel allocation, and power levels required for the WLAN to meet expected user demands. Our numerical results illustrate that the capacity based approach is more appropriate for the design of WLAN systems than those of traditional coverage based designs.

/pdf/next-generation-wireless-lan-system-design-38hegiqe8h.pdf

Next generation wireless LAN system design

The energy consumption rate for sensors in a wireless sensor network vary greatly depending on the protocols the sensors use for communication. The gossip-based sleep protocol (GSP) (X. Hou et al., 2004) is an example of a protocol that implements routing and some MAC functions in an effort to conserve energy. Simulations show that GSP can conserve energy. We expand on this effort by building a prototype system and measuring energy consumption rates. GSP was implemented on the Mica2 platform and measurements were conducted to determine energy consumption. The measurements were then used to build an energy consumption model for GSP

Measuring Energy Consumption in Wireless Sensor Networks Using GSP

Wireless sensor networks must measure environmental conditions, such as temperature, over extended periods and therefore require a long system lifetime. The design of long lifetime networks in turn requires efficient sensor node circuits, algorithms, and protocols. Protocols such as GSP (Gossip-based Sleep Protocol) have been shown to mitigate energy consumption in idle listening and receiving, by turning off the receiver circuit. However, previous studies of network lifetime have been based on physical topologies in which nodes were placed on a square grid or randomly distributed throughout the service area. This paper shows that the lifetime of a sensor network depends on the physical topology of the sensor nodes. The lifetime of a sensor network varies as a function of both the size of the network and the transmission range of individual nodes.

The Effect of Physical Topology on Wireless Sensor Network Lifetime

The explosive recent growth in Wireless Local Area Network (WLAN) deployment has generated considerable interest among network designers. Previous design approaches have mostly focused on coverage based optimization or the application of trial and error strategies. These only ensure that adequate signal strength is maintained in the intended service area. WLAN service environments, however, require a network designed to provide not only radio coverage but also adequate capacity (data rate) across the service area so that it can carry traffic load from a large number of users with certain Quality of Service (QoS) requirements. Thus, current design techniques are insufficient to provide data communication services to WLAN users. 
In this dissertation, a novel approach to the WLAN design problem is proposed that takes into account user population density in the service area, traffic demand characteristics and the structure of the service area. The resulting demand-based WLAN design results in a network that provides adequate radio signal coverage and the required data rate capacity to serve expected user traffic demand in the service region. The demand-based WLAN design model is formulated as a Constraint Satisfaction Problem (CSP). An efficient heuristic solution technique is developed to solve the CSP network design problem in reasonable computational time. The solution provides the number of access points required and the parameters of each access point, including location, frequency channel, and power level. 
Extensive numerical studies have been reported for various service scenarios ranging from a single floor with small and large service areas to a multiple floor design to a design that includes outside areas. The results of these studies illustrate that the demand-based WLAN design approach is more appropriate for the design of the WLAN systems than are existing coverage based design approaches. Additionally, extensive sensitivity analysis was conducted to study the effects of user activity level (traffic load), shadow fading, and the use of different path loss models in network design.

Joseph Kabara

Papers

MAC Protocols Used by Wireless Sensor Networks and a General Method of Performance Evaluation

Next generation wireless LAN system design

Measuring Energy Consumption in Wireless Sensor Networks Using GSP

The Effect of Physical Topology on Wireless Sensor Network Lifetime

Demand-based network planning for wlans