End-to-end versus hop-by-hop soft state refresh for multi-hop signalling systems

To ensure state synchronization of signalling operations, many signaling protocol designs choose to establish “soft” state that expires if it is not refreshed. The approaches of refreshing state in multi-hop signaling system can be classified as either end-to-end (E2E) or hop-by-hop (HbH). Although both state refresh approaches have been widely used in practical signaling protocols, the design tradeoffs between state synchronization and signaling cost have not yet been fully investigated. In this paper, we investigate this issue from the perspectives of state refresh and state removal. We propose simple but effective Markov chain models for both approaches and obtain closed-form solutions which depict the state refresh performance in terms of state consistency and refresh message rate, as well as the state removal performance in terms of state removal delay. Simulations verify the analytical models. It is observed that the HbH approach yields much better state synchronization at the cost of higher signaling cost than the E2E approach. While the state refresh performance can be improved by increasing the values of state refresh and timeout timers, the state removal delay increases largely for both E2E and HbH approaches. The analysis here shed lights on the design of signaling protocols and the configuration of the timers to adapt to changing network conditions.

End-to-end versus hop-by-hop state refresh in soft state signaling protocols

The concept of soft state (i.e., the state that will expire unless been refreshed) has been widely used in the design of network signaling protocols. The approaches of refreshing state in multi-hop networks can be classified to end-to-end (E2E) and hop-by-hop (HbH) refreshes. In this article we propose an effective Markov chain based analytical model for both E2E and HbH refresh approaches. Simulations verify the analytical models, which can be used to study the impacts of link characteristics on the performance (e.g., state synchronization and message overhead), as a guide on configuration and optimization of soft state signaling protocols. © 2009 IEEE.

Cost-effective upgrade of WDM all-optical networks using overlay fibres and hop reduction links

Fibre overlay is a cost-effective technique to alleviate wavelength blocking in some links of a wavelength-routed optical network by increasing the number of wavelengths in those links. In this letter, we investigate the effects of overlaying fibre in an all-optical network (AON) based on GÉANT2 topology. The constraint-based routing and wavelength assignment (CB-RWA) algorithm locates where cost-efficient upgrades should be implemented. Through numerical examples, we demonstrate that the network capacity improves by 25 per cent by overlaying fibre on 10 per cent of the links, and by 12 per cent by providing hop reduction links comprising 2 per cent of the links. For the upgraded network, we also show the impact of dynamic traffic allocation on the blocking probability. Copyright © 2010 John Wiley & Sons, Ltd.

Cost-effective upgrade of WDM all-optical networks using overlay fibres and hop reduction links

Fibre overlay is a cost-effective technique to alleviate wavelength blocking in some links of a wavelength-routed optical network by increasing the number of wavelengths in those links. In this letter, we investigate the effects of overlaying fibre in an all-optical network (AON) based on GÉANT2 topology. The constraint-based routing and wavelength assignment (CB-RWA) algorithm locates where cost-efficient upgrades should be implemented. Through numerical examples, we demonstrate that the network capacity improves by 25 per cent by overlaying fibre on 10 per cent of the links, and by 12 per cent by providing hop reduction links comprising 2 per cent of the links. For the upgraded network, we also show the impact of dynamic traffic allocation on the blocking probability. Copyright © 2010 John Wiley & Sons, Ltd.

Cramer-Rao bound analysis of location estimation in multi-hop wireless sensor networks

Location estimation is important for wireless sensor network (WSN) applications. In this paper we propose a Cramer-Rao Bound (CRB) based analytical approach for two centralized multi-hop localization algorithms to get insights into the error performance and its sensitivity to the distance measurement error, anchor node density and placement. The location estimation performance is compared with four distributed multi-hop localization algorithms by simulation to evaluate the efficiency of the proposed analytical approach. The numerical results demonstrate the complex tradeoff between the centralized and distributed localization algorithms on accuracy, complexity and communication overhead. Based on this analysis, an efficient and scalable performance evaluation tool can be designed for localization algorithms in large scale WSNs, where simulation-based evaluation approaches are impractical. © 2013 IEEE.

Energy-efficient multihop cooperative MISO transmission with optimal hop distance in wireless ad hoc networks

In this paper, we investigate the hop distance optimization problem in ad hoc networks where cooperative multiinput- single-output (MISO) is adopted to improve the energy efficiency of the network. We first establish the energy model of multihop cooperative MISO transmission. Based on the model, the energy consumption per bit of the network with high node density is minimized numerically by finding an optimal hop distance, and, to get the global minimum energy consumption, both hop distance and the number of cooperating nodes around each relay node for multihop transmission are jointly optimized. We also compare the performance between multihop cooperative MISO transmission and single-input-single-output (SISO) transmission, under the same network condition (high node density). We show that cooperative MISO transmission could be energyinefficient compared with SISO transmission when the path-loss exponent becomes high. We then extend our investigation to the networks with varied node densities and show the effectiveness of the joint optimization method in this scenario using simulation results. It is shown that the optimal results depend on network conditions such as node density and path-loss exponent, and the simulation results are closely matched to those obtained using the numerical models for high node density cases.