Optical Burst Switching (OBS) is one of the most promising switching technologies for next generation optical networks. As delay-sensitive applications such as Voice-over-IP (VoIP) have recently become popular, OBS networks should guarantee stringent Quality of Service (QoS) requirements for such applications. Thus, this paper proposes an Adaptive Loss-aware Flow Control (ALFC) scheme, which adaptively decides on the burst offset time based on loss-rate information delivered from core nodes for assigning a high priority to delay-sensitive application traffic. The proposed ALFC scheme also controls the upper-bounds of the factors inducing delay and jitter for guaranteeing the delay and jitter requirements of delay-sensitive application traffic. Moreover, a piggybacking method used in the proposed scheme accelerates the guarantee of the loss, delay, and jitter requirements because the response time for flow control can be extremely reduced up to a quarter of the Round Trip Time (RTT) on average while minimizing the signaling overhead. Simulation results show that our mechanism can guarantee a 10-3 loss-rate under any traffic load while offering satisfactory levels of delay and jitter for delay-sensitive applications.

Network survivability is one of the most pivotal issues in optical WDM networks. In particular, if a conduit is cut, approximately 16 terabits per millisecond can be lost in recent technology. A huge loss even by a single conduit failure fatally damages the performance and operation of the whole network. In this paper, we propose a new heuristic algorithm, called the Generalized Minimum-Cost (GMC) selection algorithm, to choose a pair of working and backup path which firstly minimizes total number of required wavelengths of working and backup path and secondly distributes lightpath request traffic into whole network links, if there are several pairs to require the same number of minimum wavelengths, in order to achieve load-balancing effect. GMC selection algorithm contains several formulas to get Working and Backup path Reservation Cost (WBRC) which can be obtained through heuristic GMC function. By using WBRC, our GMC selection algorithm achieves superior performance compared to the current Combined Min-Cost (CMC) selection algorithm and random selection algorithm in terms of the amount of wavelength consumption and blocked lightpath requests, especially on the relatively less-connected New Jersey LATA and 28-node US networks. Furthermore, we suggest a maximum number of non-blocked lightpath requests against single link failure in simulated networks for network operators to consider acceptable maximum traffic on their networks, so that they can provide 100% restoration capability in a single link failure without lightpath request blocking. We also analyze the complexity of the GMC selection algorithm and verify that the complexity of the GMC selection algorithm is lower than that of the CMC selection algorithm if the number of lightpath requests is sufficiently large.

In Wireless Sensor Networks (WSNs), sensor nodes consume their limited battery energy to send and receive data packets for data transmission. If some sensor nodes transmit data packets more frequently due to imbalance in the network topology or traffic flows, they experience higher energy consumption. And if the sensor nodes are not recharged, they will be turned off from the lack of battery energy which will degrade network sustainability. In order to resolve this problem, this paper proposes an Energy-aware MAC Protocol (EMP), which adaptively decides on the size of the channel polling cycle consisting of the sleep state (not to communicate with its target node) and the listening state (to awaken to receive data packets), according to the network traffic condition. Moreover, in accordance with the remaining energy state of the sensor node, the minimum size of the channel polling cycle is increased for better energy saving. For performance evaluation and comparison, we develop a Markov chain-based analytical model and an event-driven simulator. Simulation results show that a sensor node with EMP effectively reduces its energy consumption in imbalanced network condition and traffic flows, while latency somewhat increases under insufficient remaining energy. As a consequence, a holistic perspective for enhanced network sustainability can be studied in consideration of network traffic condition as well as the remaining energy states of sensor nodes.