Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Investigation of managerial capabilities and challenges of a core plant role

The competiveness within the global market has forced large manufacturing companies to reorganize their global operations. To act proficiently abroad is therefore no longer a choice but an important prerequisite. In global production networks, there are different plant roles that serve different purposes. One of the important roles within these networks is the core plant role. There are limited amount of the researches done regarding the core plant role. There is also a lack of consistency regarding the definition of the core plant role. It is also evident that there is a knowledge gap regarding the managerial aspects of this plant role both in the academia and in the industry. Managing a core plant requires certain capabilities. It is important to target this knowledge gap since global manufacturing is becoming a common norm for large enterprises and the importance of the core plant role is getting more evident. There is also a lack of understanding towards the challenges that a core plant must deal with both within the organization and globally towards the other plants within the manufacturing network. To address this knowledge gap further, two research questions were created ―What key capabilities are required in order to manage the core plant role?” (RQ1) and ―What are the main challenges in managing the core plant role?” (RQ2). Case study was chosen as the research method for this study since it is the most appropriate method when investigating a phenomenon in its own context. Interviews were the main research technique used to collect data. 18 semi-structured interviews were conducted in eight different cases. A literature review was conducted and was the foundation for the interview guide used in the interviews and for the data analysis. The results show that various capabilities are important for the management of the core plant role. Proximity to R&D and knowledge were the most emphasized factors. For the main challenges in terms of managing a core plant, the communication, cooperation and coordination where the most challenging aspects. Based upon finding, two frameworks have been proposed a concluding generalization and contribution of this research study. The study provides a generalization based upon data that has been collected from companies from different industries. These findings are a contribution towards both the large enterprises operating globally and the academia. 

Capabilities : describing what services can do

The ability of agents and services to automatically locate and interact with unknown partners is a goal for both the semantic web and web services. This, \serendipitous interoperability", is hindered by the lack of an explicit means of describing what services (or agents) are able to do, that is, their capabilities. At present, informal descriptions of what services can do are found in \documentation" elements; or they are somehow encoded in operation names and signatures. We show, by ref- erence to existing service examples, how ambiguous and imprecise capa- bility descriptions hamper the attainment of automated interoperability goals in the open, global web environment. In this paper we propose a structured, machine readable description of capabilities, which may help to increase the recall and precision of service discovery mechanisms. Our capability description draws on previous work in capability and process modeling and allows the incorporation of external classi¯cation schemes. The capability description is presented as a conceptual meta model. The model supports conceptual queries and can be used as an extension to the DAML-S Service Pro¯le.