Wireless ad-hoc networks are typically deployed in a decentralized way, without an authority that determines the location of nodes or the time they join the network. Additionally, existing nodes may fail during network lifetime. Consequently, the geographical span (area) of the network is irregular and unknown. However, if known, this information can be used to improve efficiency of many wireless applications; in some existing applications this information is necessary for their operation in the real use cases. For this purpose, we propose a distributed algorithm that determines the geographical network area. It is the first algorithm that simultaneously discovers network border, approximates the network area with a data structure of a constant size, and disseminates this information to all network nodes. Our algorithm uses only the nodes' local information, has a constant computational complexity and is resilient to link unreliability. The algorithm is evaluated by simulation on realistic network topologies of different sizes. The simulations demonstrate that the algorithm has high accuracy in its estimation of the network area, scales well with the number of nodes, and that it creates a low communication overhead.

In the world where on-demand and trustworthy service delivery is one of the main preconditions for successful business, service and business process availability is of the paramount importance and cannot be compromised. For that reason service availability is coming into central focus of the IT operations and management research and practice. Still, our understanding of service and process availability is mostly empirical and at best, sketchy. Services are assessed using a mixture of qualitative, quantitative, and analytical methods, with results of varying quality. We introduce a systematic model-based methodology and a tool for service and business process availability assessment. The main advantage of the proposed method is the ability to automatically generate availability models, based on the service/process description and technical infrastructure it is executing on. Therefore, service level agreements can be tested/simulated or return on investment calculation can be performed, without the need for costly experiments and/or actual investments.

We analyze accuracy of hysteresis link status detectors in static and mobile wireless multi-hop networks (WMNs), with focus on errors in link status detection caused by the unreliable communication channel. The hysteresis link status detectors are of particular importance in WMNs due to their use in various protocols, such as AODV and OLSR. Stochastic models are derived that describe hysteresis link status detector behavior as a function of detector parameters and network characteristics. Models are applied to a real network and their analysis shows that the probability of errors in link status detection in WMNs is considerable. In order to reduce these errors, we optimize detector parameters so that the link detection error probability is minimized.

We extend the Breadth First Search (BFS) algorithm to use it for cut-edge(bridge) detection in graphs. The changes in the algorithm are tailored such that the algorithm can be applied in wireless multihop networks: e.g., it fully utilizes the broadcasting nature of the wireless medium. The distributed BFS algorithm (flooding) is widely used for route discovery and information dissemination in wireless multihop networks (WMNs) so the overhead introduced by our bridge detection algorithm is limited - the network is already performing the distributed BFS and we reuse the information from it to detect the bridges.

We have developed a mathematical model for calculation of expected value of share of edges being dropped while constructing a Gabriel or a relative neighborhood graph starting from a random geometrical graph created by a homogeneous Poisson point process on a plane. The expressions for the expected values of number of faces and face size are derived as well. All expressions are given as functions of deployment configuration. The results are verified through detailed comparison with extensive simulation results. Since Gabriel and relative neighborhood graphs are used for various applications in ad hoc networking we believe that our model simplifies theoretical analysis of functionality and performance of such networks