Economic incentive patterns and their application to ad hoc networks

While research about cooperation incentives for mobile ad hoc networks (MANETs) is done only for a relative short period, there exists tremendous knowledge in the economic and social areas. Based on a new categorization of incentive patterns, we examine the relevant properties of each pattern and demonstrate their respective design alternatives and occurring challenges for the application to ad hoc networks. With a focus on trade based patterns, we found that negotiation about actions proves to be very complex or inefficient in MANETs. Another approach, the introduction of an artificial currency, also implies several problems like how to equip the entities with means of payment and how to secure liquidity. As a novelty, we introduce a new kind of incentive pattern following the concept of company shares. It suits well for MANETs because it can be shown that through the creation of individual currencies the above mentioned problems disappear

Provision of adaptive and context-aware service discovery for the Internet of Things

The IoT concept has revolutionised the vision of the future Internet with the advent of standards such as 6LoWPAN making it feasible to extend the Internet into previously isolated environments, e.g., WSNs. The abstraction of resources as services, has opened these environments to a new plethora of potential applications. Moreover, the web service paradigm can be used to provide interoperability by offering a standard interface to interact with these services to enable WoT paradigm. However, these networks pose many challenges, in terms of limited resources, that make the adaptability of existing IP-based solutions infeasible. As traditional service discovery and selection solutions demand heavy communication and use bulky formats, which are unsuitable for these resource-constrained devices incorporating sleep cycles to save energy. Even a registry based approach exhibits burdensome traffic in maintaining the availability status of the devices. The feasible solution for service discovery and selection is instrumental to enable the wide application coverage of these networks in the future. This research project proposes, TRENDY, a new compact and adaptive registry-based SDP with context awareness for the IoT, with more emphasis given to constrained networks, e.g., 6LoWPAN It uses CoAP-based light-weight and RESTful web services to provide standard interoperable interfaces, which can be easily translated from HTTP. TRENDY's service selection mechanism collects and intelligently uses the context information to select appropriate services for user applications based on the available context information of users and services. In addition, TRENDY introduces an adaptive timer algorithm to minimise control overhead for status maintenance, which also reduces energy consumption. Its context-aware grouping technique divides the network at the application layer, by creating location-based groups. This grouping of nodes localises the control overhead and provides the base for service composition, localised aggregation and processing of data. Different grouping roles enable the resource-awareness by offering profiles with varied responsibilities, where high capability devices can implement powerful profiles to share the load of other low capability devices. Thus, it allows the productive usage of network resources. Furthermore, this research project proposes APPUB, an adaptive caching technique, that has the following benefits: it allows service hosts to share their load with the resource directory and also decreases the service invocation delay. The performance of TRENDY and its mechanisms is evaluated using an extensive number of experiments performed using emulated Tmote sky nodes in the COOJA environment. The analysis of the results validates the benefit of performance gain for all techniques. The service selection and APPUB mechanisms improve the service invocation delay considerably that, consequently, reduces the traffic in the network. The timer technique consistently achieved the lowest control overhead, which eventually decreased the energy consumption of the nodes to prolong the network lifetime. Moreover, the low traffic in dense networks decreases the service invocations delay, and makes the solution more scalable. The grouping mechanism localises the traffic, which increases the energy efficiency while improving the scalability. In summary, the experiments demonstrate the benefit of using TRENDY and its techniques in terms of increased energy efficiency and network lifetime, reduced control overhead, better scalability and optimised service invocation time

Engineering self-managed adaptive networks

In order to meet the requirements of emerging services, the future Internet will need to be flexible, reactive and adaptive with respect to arising network conditions. Network management functionality is essential in providing dynamic reactiveness and adaptability but current management approaches have limitations which prevent them from meeting these requirements. In search for a paradigm shift, recent research efforts have been focusing on autonomic/self-management principles, whereby network elements can adapt themselves to contextual changes without any external intervention through adaptive and flexible functionality. This thesis investigates how autonomic principles can be extended and applied to fixed networks for quality of service and performance management. It presents a novel resource management framework which enables intelligence to be introduced within the network in order to support self-management functionality in a coordinated and controllable manner. The proposed framework relies on a distributed infrastructure, called the management substrate, which is a logical structure formed by the ingress nodes of the network. The role of the substrate is illustrated on realistic resource management application scenarios for the emerging self-managed Internet. These cover solutions for dynamic traffic engineering (load balancing across multiple paths), energy efficiency and cache management in Internet Service Providers. The thesis addresses important research challenges associated with the proposed framework, such as the design of specific organisational, communication and coordination models required to support the different management control loops. Furthermore, it develops, for each application scenario, specific mechanisms to realise the relevant resource management functionality. It also considers issues related to the coexistence of multiple control loops and investigates an approach by which their interactions can be managed. In order to demonstrate the benefits of the proposed resource management solution, an extensive performance evaluation of the different mechanisms described in this thesis have been performed based on realistic traffic traces and network topologies

Distributed resource discovery: architectures and applications in mobile networks

As the amount of digital information and services increases, it becomes increasingly important to be able to locate the desired content. The purpose of a resource discovery system is to allow available resources (information or services) to be located using a user-defined search criterion. This work studies distributed resource discovery systems that guarantee all existing resources to be found and allow a wide range of complex queries. Our goal is to allocate the load uniformly between the participating nodes, or alternatively to concentrate the load in the nodes with the highest available capacity. The first part of the work examines the performance of various existing unstructured architectures and proposes new architectures that provide features especially valuable in mobile networks. To reduce the network traffic, we use indexing, which is particularly useful in scenarios, where searches are frequent compared to resource modifications. The ratio between the search and update frequencies determines the optimal level of indexing. Based on this observation, we develop an architecture that adjusts itself to changing network conditions and search behavior while maintaining optimal indexing. We also propose an architecture based on large-scale indexing that we later apply to resource sharing within a user group. Furthermore, we propose an architecture that relieves the topology constraints of the Parallel Index Clustering architecture. The performance of the architectures is evaluated using simulation. In the second part of the work we apply the architectures to two types of mobile networks: cellular networks and ad hoc networks. In the cellular network, we first consider scenarios where multiple commercial operators provide a resource sharing service, and then a scenario where the users share resources without operator support. We evaluate the feasibility of the mobile peer-to-peer concept using user opinion surveys and technical performance studies. Based on user input we develop access control and group management algorithms for peer-to-peer networks. The technical evaluation is performed using prototype implementations. In particular, we examine whether the Session Initiation Protocol can be used for signaling in peer-to-peer networks. Finally, we study resource discovery in an ad hoc network. We observe that in an ad hoc network consisting of consumer devices, the capacity and mobility among nodes vary widely. We utilize this property in order to allocate the load to the high-capacity nodes, which serve lower-capacity nodes. We propose two methods for constructing a virtual backbone connecting the nodes