This paper presents a model of the connectivity of a wireless sensor network (WSN) deployed over a square area, which considers border effects. This model supports an accurate evaluation of the reliability of the network with and without node failures. Using the proposed model we analyze the tradeoff between the number of sensors and their communication range when deploying a wireless network that is connected with high probability and validate this analysis through simulation experiments. Additional simulations, considering sensor failures, ratified that periodic sensor redeployments, calculated according to the proposed model, can extend the reliability of WSNs, keeping them connected with high probability. For applications that can withstand temporary network disconnection, we obtained theoretical and experimental evidence that the proposed model also supports the calculation of a less frequent redeployment procedure that provides network connectivity at high levels of availability. Finally, extending the approach to a circular shaped area was considered.

Introduces a nested-predicate scheme for fault tolerance, called Nest. Nest provides a formal comprehensive model for fault-tolerant parallel algorithms and a general methodology for designing reliable applications for multiprocessor systems. The model relies on the formalization of concepts for fault tolerance by means of three nested system predicates and on properties ruling their interrelationships. This rigorous framework facilitates the study of the specific properties that enable an algorithm to tolerate faults. The consequence of that is the outline of systematic design techniques that can be used to add fault tolerance properties to algorithms while preserving their functional characteristics.>

A class of algorithms suitable for fault-tolerant execution in multiprocessor systems by exploiting the existing embedded redundancy in the problem variables is characterized. Because of this unique property, no extra computations need be superimposed on the algorithm in order to provide redundancy for fault recovery, as well as fault detection in some cases. A forward recovery scheme is thus used with very low time overhead. The method is applied to the implementation of two iterative algorithms: solution of Laplace equations by Jacobi's method and the calculation of the invariant distribution of a Markov chain. Experiments show less than 15% performance degradation for significant problem instances in fault-free situations, and as low as 2.43% in some cases. The extra computation time needed for locating and recovering from a detected fault does not exceed the time necessary to execute a single iteration. The fault-detection procedures provide fault coverage close to 100% for faults causing errors that affect the correctness of the computations.>

The strengths and weaknesses of existing size estimation techniques are discussed. The nature of software size estimation is considered. The proposed method takes advantage of a characteristic of object-oriented systems, the natural correspondence between specification and implementation, in order to enable users to come up with better size estimates at early stages of the software development cycle. Through a statistical approach the method also provides a confidence interval for the derived size estimates. The relation between the presented software sizing model and project cost estimation is also considered.>