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We study the throughput capacity and transport capacity for both random and arbitrary wireless networks under Gaussian Channel model when all wireless nodes have the same constant transmission power P and the transmission rate is determined by Signal to Interference plus Noise Ratio (SINR). We consider networks with n wireless nodes $$\{v_1,v_2,\ldots,v_n\}$$ (randomly or arbitrarily) distributed in a square region B with a side-length a. We randomly choose n node as the source nodes of n multicast sessions. For each source node v, we randomly select k points and the closest k nodes to these points as destination nodes of this multicast session. We derive achievable lower bounds and some upper bounds on both throughput capacity and transport capacity for both unicast sessions and multicast sessions. We found that the asymptotic capacity depends on the size a of the deployment region, and it often has three regimes. [ABSTRACT FROM AUTHOR]

Providing Quality of Service (QoS) is a major challenge in wireless networks. In this paper we propose a distributed call admission control protocol (DCAC) to do both bandwidth and delay guaranteed call admission for multihop wireless mesh backbone networks, by exploiting the multi-channel multi-radio (mc-mr) feature. We propose a novel routing metric for route setup, and present an efficient distributed algorithm for link reservation that satisfies the required bandwidth and reduces the delay by a local scheduling that minimizes one hop delay. To the best of our knowledge, this is the first distributed protocol that embeds mc-mr feature in Time Division Medium Access (TDMA) to do QoS call admission in wireless backbone networks. Extensive simulation studies show that our protocol significantly improves network performance on supporting QoS sessions compared with some widely used protocols. [ABSTRACT FROM AUTHOR]

Abstract We consider a wireless network composed of a set of n wireless nodes distributed in a two dimensional plane. The signal sent by every node can be received by all nodes within its transmission range, which is uniform and normalized to one unit. We present the first distributed method to construct a bounded degree planar connected structure LRNG, whose total link length is within a constant factor of the minimum spanning tree using total O(n) messages under the broadcast communication model. Moreover, in our method, every node only uses its two-hop information to construct such structure, i.e., it is localized method. We show that some two-hop information is necessary to construct any low-weighted structure. We also study the application of this structure in efficient broadcasting in wireless ad hoc networks. We prove that, for broadcasting, the relative neighborhood graph (RNG), which is the previously best-known sparse structure that can be constructed locally, could use energy O(n) times the total energy used by our structure LRNG. Our simulations show that the broadcasting based on LRNG consumes energy about 36% more than that by MST, and broadcasting based on RNG consumes energy about 64% more than that by MST. We also show that no localized method can construct a structure for broadcasting with total power consumption asymptotically better than LRNG. [ABSTRACT FROM AUTHOR]

Abstract Wireless network topology control has drawn considerable attention recently. Priori arts assumed that the wireless ad hoc networks are modeled by unit disk graphs (UDG), i.e., two mobile hosts can communicate as long as their Euclidean distance is no more than a threshold. However, practically, the networks are never so perfect as unit disk graphs: the transmission ranges may vary due to various reasons such as the device differences, the network control necessity, and the perturbation of the transmission ranges even the transmission ranges are set as the same originally. Thus, we assume that each mobile host has its own transmission range. The networks are modeled by mutual inclusion graphs (MG), where two nodes are connected iff they are within the transmission range of each other. Previously, no method is known for topology control when the networks are modeled as mutual inclusion graphs. [ABSTRACT FROM AUTHOR]