Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner

Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT ‘things’. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through non-congested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes’ sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications’ sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL

Load Repartition for Congestion Control in Multimedia Wireless Sensor Networks with Multipath Routing

Wireless sensor networks hold a great potential in the deployment of several applications of a paramount importance in our daily life. Video sensors are able to improve a number of these applications where new approaches adapted to both wireless sensor networks and video transport specific characteristics are required. The aim of this work is to provide the necessary bandwidth and to alleviate the congestion problem to video streaming. In this paper, we investigate various load repartition strategies for congestion control mechanism on top of a multipath routing feature. Simulations are performed in order to get insight into the performances of our proposals

Congestion Control By Using Adaptive Data Rate Technique with High Bandwidth in Wireless Sensor Networks

Wireless sensor network one of the most favourite topic for researcher to explore. Wireless sensor networks is very useful so more number of sensor nodes are deploying and large number of data being sensed and collected. To meet the expectations of demands networks should be in safe and good state. Problems in wireless sensor networks are congestion and wastage of energy. So it's necessary to control the congestion and minimize the energy consumption. Congestion causes heavy data loss and unnecessary retransmission of data. Congestion causes by many reasons. There are some techniques and algorithms which can control the congestion at some degree. Here we have suggested technique which can do a Congestion Control with High bandwidth in networks. Amount of congestion in network can be decided by maximum and minimum threshold values that can assign in initial phase of algorithm

JTP: An Energy-conscious Transport Protocol for Wireless Ad Hoc Networks

Within a recently developed low-power ad hoc network system, we present a transport protocol (JTP) whose goal is to reduce power consumption without trading off delivery requirements of applications. JTP has the following features: it is lightweight whereby end-nodes control in-network actions by encoding delivery requirements in packet headers; JTP enables applications to specify a range of reliability requirements, thus allocating the right energy budget to packets; JTP minimizes feedback control traffic from the destination by varying its frequency based on delivery requirements and stability of the network; JTP minimizes energy consumption by implementing in-network caching and increasing the chances that data retransmission requests from destinations "hit" these caches, thus avoiding costly source retransmissions; and JTP fairly allocates bandwidth among flows by backing off the sending rate of a source to account for in-network retransmissions on its behalf. Analysis and extensive simulations demonstrate the energy gains of JTP over one-size-fits-all transport protocols.Defense Advanced Research Projects Agency (AFRL FA8750-06-C-0199

TCP-Aware Backpressure Routing and Scheduling

In this work, we explore the performance of backpressure routing and scheduling for TCP flows over wireless networks. TCP and backpressure are not compatible due to a mismatch between the congestion control mechanism of TCP and the queue size based routing and scheduling of the backpressure framework. We propose a TCP-aware backpressure routing and scheduling that takes into account the behavior of TCP flows. TCP-aware backpressure (i) provides throughput optimality guarantees in the Lyapunov optimization framework, (ii) gracefully combines TCP and backpressure without making any changes to the TCP protocol, (iii) improves the throughput of TCP flows significantly, and (iv) provides fairness across competing TCP flows