The last years have been characterized by an increasing interest in the grid and cloud computing that allow the implementation of high performance computing structures in a distributed way by exploiting multiple processing resources. The presence of mobile terminals has extended the paradigm to the so called pervasive grid networks, where multiple heterogeneous devices are interconnected to form a distributed computing resource. In such a scenario, there is the need of efficient techniques for providing reliable wireless connections among network nodes. This paper deals with the proposal of a suitable resource management scheme relying on a routing algorithm able to perform jointly the resource discovery and task scheduling for implementing an efficient pervasive grid infrastructure in a wireless ad hoc scenario. The proposed solutions have been considered within two different parallelization processing schemes, and their effectiveness has been verified by resorting to computer simulations.(nodes) able to consider specific application requests for the implementation of a service in a distributed manner according to the pervasive grid computing principle [7][8][9].In the classical grid computing paradigm, the processing nodes are high performance computers or multicore workstations, usually organized in clusters and interconnected through broadband wired communication networks with small delay and high reliability (e.g., fiber optic, DSL lines), thus they can be considered as a quasi-ideal communication link. The pervasive grid computing paradigm overcomes the limits of the classical grid approach, allowing the processing of distributed applications on heterogeneous devices interconnected by heterogeneous communication technologies by exploiting recent advances in wireless technologies as higher bandwidths, reduced delays, and higher reliability. In this way, we can resort to a computing cloud composed by fixed or mobile nodes (e.g., smartphones, PDAs, laptops) interconnected through broadband networks where the nodes share and concur to a grid computing processing. A pervasive grid computing system has to be supported by suitable techniques to discover and organize heterogeneous resources,