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In wireless networks, important network functionalities such as power control, rate allocation, routing, and congestion control must be optimized in a coherent and integrated manner. In this work, an interference-limited wireless network is considered, whereby power control and routing variables are chosen to minimize the sum of link costs which depend on both link capacities and link flow rates. The necessary conditions for optimality are established. These conditions are sufficient for optimality if link cost functions are jointly convex, and imply Pareto optimality if link costs are strictly quasi-convex. Network algorithms based on the scaled gradient projection method, where power control and routing are performed on a node-by-node basis, are presented. For these algorithms, explicit scaling matrices and stepsizes are found which lead to more distributed implementation, and which guarantee fast convergence to a network configuration satisfying the optimality conditions, starting from any initial configuration with finite cost. Refinements of the algorithms for more accurate link capacity models are presented, and the results are extended to wireless networks where the physical-layer rate region is given by an arbitrary convex set. Finally, it is shown that the power control and routing algorithms can naturally be extended to incorporate congestion control. Index Terms--Congestion control, cross-layer optimization, distributed algorithms, multihop wireless networks, power control, routing.

A hybrid wireless network is an extension to an infrastructure network, where a mobile host may connect to an access point (AP) using multihop wireless routes via other mobile hosts. The APs are configured to operate on one of multiple available channels. Mobile hosts and wireless routers can select their operating channels dynamically through channel switching. In this environment, we propose a routing protocol that finds routes to balance load among channels while maintaining connectivity. The protocol works with nodes equipped with a single network interface, which distinguishes our work with other multichannel routing protocols that require multiple interfaces per node. The protocol discovers multiple routes to multiple APs, possibly operating on different channels. Based on traffic load information, each node selects the 'best' route to an AP and synchronizes its channel with the AP. With this behavior, the channel load is balanced, removing hot spots and improving channel utilization. The protocol assures that every node has at least one route to an AP, where all intermediate nodes are operating on the same channel. Our simulation results show that the proposed protocol successfully adapts to changing traffic conditions and improves performance over a single-channel protocol and a multichannel protocol with no load balancing. Index Terms--Communication system routing, communication systems, load-balancing, multi-channel, multi-hop, protocols, routing.

This paper presents a scalable routing protocol for very large and dense ad hoc networks. The scalability of ad hoc networks is becoming an important issue due to the increasing number of applications in a distributed environment, the great number of mobile nodes involved into communication and wide speed range in which the mobile nodes can move. It is important to offer scalability in terms of network size, traffic load and mobility speed. The proposed protocol, called Geo-LANMAR, inherits the same advantage of LANMAR protocol in terms of group motion support and traffic load scalability and it reflects also the behaviour of geo-routing protocols such as GPSR. Geo-LANMAR is based on the idea of Terminodes routing for the forwarding scheme: long-distance geo-forwarding and low-distance table-driven routing. Its updating scheme, instead, is similar to the Hazy Sighted Link State Routing (HSLS) through a spatial and time update rate differentiation: frequent update rate for short distance and lower update rate for long distance. Performance evaluation of Geo-LANMAR has been lead out and a comparison in terms of throughput, average end-to-end delay and control overhead has been conducted against other well-known protocols such as LANMAR, GPSR and AODV. Geo-LANMAR results scalable in terms of traffic load, mobility speed, number of nodes and number of groups. Keywords: Geo-LANMAR; Geo-routing; Scalable; HSLS; GPSR; Terminodes routing

In this paper we consider the problem of routing deterministic arriving jobs to parallel servers with deterministic (distinct) service times, where we assume that the arrival rate of the jobs [...]

Dominating-set-based routing in ad hoc wireless networks with unidirectional links is examined and discussed.

The concept of a restricted area for conducting message routing and balancing buffer utilization is proposed. The aim is to minimize traffic congestion.

The High-Performance Efficient Router (HiPER), a multidimensional router that accommodates high-throughput error-corrected communication channels, is discussed. HiPER combines flit-level error control and mad postman (bit-pipelined) switching.

A single, unified theory is described for design of deadlock-free fully adaptive routing algorithms for all classes of network topologies and all switching procedures. A general theory is proposed that applies to direct and indirect networks, and to regular and irregular networks.

Localized routing algorithms are discussed, which aim to minimize the total energy per packet and/or the lifetime of each node. Power consumption in static networks is a primary focus of interest.

The superiority of flooding-based methods and hybrid single-path/flooding variants, compared to LAR2, is discussed. It is shown that an approach involving loop-free, single-path algorithms and guaranteed delivery is more successful than existing procedures.

A novel neural network approach called gradual neural network (GNN) is presented for segmented channel routing in field programmable gate arrays (FPGA's). FPGA's contain predefined segmented channels for net routing, where adjacent segments in a track can be interconnected through programmable switches for longer segments. The goal of the FPGA segmented channel routing problem, known to be NP-complete, is to find a conflict-free net routing with the minimum routing cost. The GNN for the N-net-M-track problem consists of a neural network of N x M binary neurons and a gradual expansion scheme. The neural network satisfies the constraints of the problem, while the gradual expansion scheme seeks the cost minimization by gradually increasing activated neurons. The energy function and the motion equation are newly defined with heuristic methods. The performance is verified through solving 30 instances, where GNN finds better solutions than existing algorithms within a constant number of iteration steps.