Quality of Service routing

Motivation

Despite MANETs are very versatile and appropriate to be used in many scenarios due to the infrastructure-less and self-organized characteristics, this kind of networks have important limitations, such as bandwidth-constrained, variable capacity links and energy-constrained operation. These limitations are imposed by the shared nature of the wireless channel, the mutual interference between nearby nodes and the resource-constrained devices. Furthermore, the dynamic topology in this kind of networks causes frequent link failures and high error rates, which makes even more difficult to maintain a desired degree of Quality of Service (QoS). With the massive demand of video content from mobile devices, it has become very necessary for MANETs to have an efficient routing and QoS mechanisms to support the transmission of multimedia content. An optimal strategy to support applications with real-time requirements could be the use of additional control mechanisms to adapt the processes of encoding, transmitting or decoding, depending on network status. However, conventional transport and routing protocols in mobile ad hoc networks do not provide a suitable connectivity service to support higher bandwidth and quality requirements. Most of the standardized routing protocols for MANETs have been designed to find a feasible route from a source to a destination without taking into account the available resources in the network or speciﬁc requirements of an application.

Therefore, the established routes using these routing protocols cannot interact with the source node to adjust the transmission rate. Consequently, the application must send its data using a fixed sending rate and cannot take advantage of the adaptation feature inherent in some coding techniques such as scalable video coding (H.264/SVC) and multiple description coding. In addition, without knowing the bottleneck throughput, the source may send much more data than the bottleneck node on the route can transmit. The overwhelmed node must drop data, which wastes a considerable amount of energy and needlessly consumes bandwidth.

Video transmission may be improved by means of additional mechanisms and cross-layer techniques in the routing protocols in order to solve or mitigate the limitations of MANETs.

Overview

One of the major challenges for the transmission of time-sensitive data over MANETs is the deployment of an end-to-end QoS support mechanism. A realistic solution for QoS provision should not separate the routing from QoS management since it can involve the selection of inefficient routes and, thus, reduce the likelihood of meeting the QoS requirements of the established communications in the ad hoc network.

The routing protocols for mobile ad hoc networks can be can be classified according to different criteria. The most common classification is based on the routing information update mechanism. Hence, routing protocols can be driven either by a routing table (proactive) or on demand (reactive). Proactive protocols always maintain up-to-date information of routes from each node to every other node in the network. Routing information is stored in the routing table of each node and route updates are propagated throughout the network to keep the routing information as recent as possible. As a consequence, there is a constant overhead due to routing traffic but there is no initial delay in data communications. Some examples of proactive routing protocols are Destination-Sequenced Distance Vector (DSDV) [1] and Optimized Link State Routing (OLSR) [2]. On the other hand, with reactive protocols the route is created only when the source requests a route to a destination or when a broken link is detected. This kind of routing protocol does not need extra control packets for maintenance, although high latency time can be generated when establishing the new route. The most important reactive routing protocols are Ad hoc On-demand Distance Vector (AODV) [3], Dynamic Source Routing (DSR) [4], Dynamic MANET On-demand (DYMO), also known as AODVv2, which is still under standardization process (draft) [5]. Additionally, there are hybrid proposals that combine the elements of proactive and reactive protocols, such as the Zone Routing Protocol (ZRP) [6], and Hybrid ant colony optimization (HOPNET) [7].

An important research line of our group is the proposal of a routing protocol called AQA-AODV (Adaptive QoS-Aware Ad-hoc On-demand Distance Vector). This protocol is based on AODV, but incorporates three new elements:

An algorithm used for the estimation of the available bandwidth that allows nodes along the path to know their available resources (in terms of bandwidth).
A cross-layer mechanism to inform to the application layer the available bandwidth by which the source node can easily adapt its transmission rate.
A new route recovery mechanism that involves the modification of the route request and the implementation of a session cache table to store information about the established sessions and its QoS conditions.

An important difference between the proposed protocol and other solutions based on AODV is the adaptive feedback scheme, integrated into the routing protocol, by which the source node can know and easily adapt its transmission rate according to the state of the route. For this reason, nodes along the path must know their available resources by using some algorithms.

Figure 1 depicts the functional block diagram of AQA-AODV. The main three elements of AQA-AODV are a bandwidth estimation module, a routing module and a route recovery module. The first module performs the estimation of the available bandwidth and provides data feedback to the video application. HELLO packets are used in the bandwidth estimation, which is periodically executed according to the trigger of Timer module. The information about the available bandwidth is used by video application in order to tune a coding parameter to compose a video stream that can be supported by network. On the other hand, the routing module receives the route requests from the application and executes the route discovery routine. When a route between source and destination is established, a unique session identifier (sid) is assigned in the Session/sid mapper. The identification data of the sessions (sid, source and destination address, QoS requirements and expiration time) are stored internally in a database, called Session Cache List. The third main module is the route recovery module, which is in charge of re-establishing the connections after a link failure, taking into account the QoS conditions of each of the sessions.

Figure 1. Functional block diagram of AQA-AODV

A list of publications of the research group in this field can be found in [8]-[14]. Also, it is possible to obtain more information about AQA-AODV in this link.

References

[1] C. Perkins and P. Bhagwat, “Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers,” in Proceedings of the Conference on Communications Architectures, Protocols and Applications, New York, NY, USA, 1994, pp. 234–244.
[2] T. Clausen and P. Jacquet, “Optimized Link State Routing Protocol (OLSR),” Network Working Group, Internet Engineering Task Force (IETF), vol. 3626, 2003.
[3] C. Perkins, E. Belding-Royer, and S. Das, “Ad hoc On-Demand Distance Vector (AODV) Routing,” Network Working Group, Internet Engineering Task Force (IETF), vol. 3561, 2003.
[4] D. Johnson, Y. Hu, and D. Maltz, “The Dynamic Source Routing Protocol (DSR) for Mobile Ad Hoc Networks for IPv4”, Network Working Group. Internet Engineering Task Force (IETF), 2007.
[5] C. Perkins, S. Ratliff, and J. Dowdell, “Dynamic MANET On-demand (AODVv2) Routing (IETF Internet Draft – 05),” Internet Engineering Task Force, 2014.
[6] P. Samar, M. R. Pearlman, and Z. J. Haas, “Independent Zone Routing: An Adaptive Hybrid Routing Framework for Ad Hoc Wireless Networks,” IEEE ACM Trans Netw, vol. 12, no. 4, pp. 595–608, Aug. 2004.
[7] J. Wang, E. Osagie, P. Thulasiraman, and R. K. Thulasiram, “HOPNET: A hybrid ant colony optimization routing algorithm for mobile ad hoc network,” Ad Hoc Netw., vol. 7, no. 4, pp. 690–705, Jun. 2009.

Related publications

[8] W. Castellanos, P. Acelas, P. Arce, and J. C. Guerri, “Evaluation of a QoS-Aware Protocol with Adaptive Feedback Scheme for Mobile Ad Hoc Networks,” in Proc. of the Int. ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE), Las Palmas (Spain), Nov. 2009, pp. 120-127.
[9] W. Castellanos, P. Arce, P. Acelas, and J. C. Guerri, “Route recovery algorithm for QoS-aware routing in MANETs,” in Lectures notes of the ICST Conference on Mobile Lightweight Wireless Systems (MOBILIGHT), Bilbao (Spain), May. 2011, vol. 8, pp. 81-93.
[10] J. C. Guerri, P. Arce, P. Acelas, W. Castellanos, and F. Fraile, “Routing and Coding Enhancements to Improve QoS of Video Transmissions in Future Ad Hoc Networks,” Multimedia Services and Streaming for Mobile Devices: Challenges and Innovations, Ed. IGI Global, pp. 244-261, 2011.
[11] W. Castellanos, J. C. Guerri, and P. Arce, “SVCEval-RA: an evaluation framework for adaptive scalable video streaming,” Multimedia Tools and Applications, doi:10.1007/s11042-015-3046-y, 2015.
[12] W. Castellanos, P. Guzmán, P. Arce, and J. C. Guerri, “Mechanisms for improving the scalable video streaming in mobile ad hoc networks,” in Proc. of ACM Int. Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN), Cancun (Mexico), Nov. 2015, pp. 33-40.
[13] W. Castellanos, J. C. Guerri, and P. Arce, “Performance evaluation of scalable video streaming in mobile ad hoc networks,” IEEE Latin American Transactions, vol. 14, no. 1, pp. 122-129, 2016.
[14] W. Castellanos, J. C. Guerri, and P. Arce, “A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks,” Computer Communications, vol. 77, pp. 10-25, 2016.