An altruistic cross-layer recovering mechanism for ad hoc wireless networks

Video streaming services have restrictive delay and bandwidth constraints. Ad hoc networks represent a hostile environment for this kind of real-time data transmission. Emerging mesh networks, where a backbone provides more topological stability, do not even assure a high quality of experience. In such scenario, mobility of terminal nodes causes link breakages until a new route is calculated. In the meanwhile, lost packets cause annoying video interruptions to the receiver. This paper proposes a new mechanism of recovering lost packets by means of caching overheard packets in neighbor nodes and retransmit them to destination. Moreover, an optimization is shown, which involves a video-aware cache in order to recover full frames and prioritize more significant frames. Results show the improvement in reception, increasing the throughput as well as video quality, whereas larger video interruptions are considerably reduced. Copyright © 2014 John Wiley & Sons, Ltd.Arce Vila, P.; Guerri Cebollada, JC. (2015). An altruistic cross-layer recovering mechanism for ad hoc wireless networks. Wireless Communications and Mobile Computing. 15(13):1744-1758. doi:10.1002/wcm.2459S174417581513Li J Blake C De Couto DSJ Lee HI Morris R Capacity of ad hoc wireless networks Proceedings of the 7th Annual International Conference on Mobile Computing and Networks (MobiCom) 2001 61 69Akyildiz, I. F., & Xudong Wang. (2005). A survey on wireless mesh networks. IEEE Communications Magazine, 43(9), S23-S30. doi:10.1109/mcom.2005.1509968Hsu, C.-J., Liu, H.-I., & Seah, W. K. G. (2011). Opportunistic routing – A review and the challenges ahead. Computer Networks, 55(15), 3592-3603. doi:10.1016/j.comnet.2011.06.021Huang, X., Zhai, H., & Fang, Y. (2008). Robust cooperative routing protocol in mobile wireless sensor networks. IEEE Transactions on Wireless Communications, 7(12), 5278-5285. doi:10.1109/t-wc.2008.060680Wieselthier, J. E., Nguyen, G. D., & Ephremides, A. (2001). Mobile Networks and Applications, 6(3), 251-263. doi:10.1023/a:1011478717164Clausen T Jacquet P Optimized Link State Routing Protocol (OLSR), IETF RFC 3626 2003 http://www.rfc-editor.org/rfc/rfc3626.txtMarina, M. K., & Das, S. R. (2006). Ad hoc on-demand multipath distance vector routing. Wireless Communications and Mobile Computing, 6(7), 969-988. doi:10.1002/wcm.432Zhou X Lu Y Ma HG Routing improvement using multiple disjoint paths for ad hoc networks International Conference on Wireless and Optical Communications Networks (IFIP) 2006 1 5Fujisawa H Minami H Yamamoto M Izumi Y Fujita Y Route selection using retransmission packets for video streaming on ad hoc networks IEEE Conference on Radio and Wireless Symposium (RWS) 2006 607 610Badis H Agha KA QOLSR multi-path routing for mobile ad hoc networks based on multiple metrics: bandwidth and delay IEEE 59th Vehicular Technology Conference (VTC) 2004 2181 2184Wu Z Wu J Cross-layer routing optimization for video transmission over wireless ad hoc networks 6th International Conference on Wireless Communications Networks and Mobile Computing (WiCOM) 2010 1 6Schier, M., & Welzl, M. (2012). Optimizing Selective ARQ for H.264 Live Streaming: A Novel Method for Predicting Loss-Impact in Real Time. IEEE Transactions on Multimedia, 14(2), 415-430. doi:10.1109/tmm.2011.2178235Nikoupour M Nikoupour A Dehghan M A cross-layer framework for video streaming over wireless ad-hoc networks 3rd International Conference on Digital Information Management (ICDIM) 2008 340 345Yamamoto R Miyoshi T Distributed retransmission method using neighbor terminals for ad hoc networks Proceedings of the 14th Asia-Pacific Conference on Communications (APCC) 2008 1 5Gravalos I Kokkinos P Varvarigos EA Multi-criteria cooperative energy-aware routing in wireless ad-hoc networks Proceedings of the 9th International Wireless Communications and Mobile Computing Conference (IWCMC) 2013 387 393Abid, R. M., Benbrahim, T., & Biaz, S. (2010). IEEE 802.11s Wireless Mesh Networks for Last-Mile Internet Access: An Open-Source Real-World Indoor Testbed Implementation. Wireless Sensor Network, 02(10), 725-738. doi:10.4236/wsn.2010.210088Yen, Y.-S., Chang, R.-S., & Wu, C.-Y. (2011). A seamless handoff scheme for IEEE 802.11 wireless networks. Wireless Communications and Mobile Computing, 13(2), 157-169. doi:10.1002/wcm.1102Liangzhong Yin, & Guohong Cao. (2006). Supporting cooperative caching in ad hoc networks. IEEE Transactions on Mobile Computing, 5(1), 77-89. doi:10.1109/tmc.2006.15Biswas S Morris R ExOR: opportunistic multi-hop routing for wireless networks Proceedings of ACM SIGCOMM 2005 133 144Chachulski S Jennings M Katti S Katabi D Trading structure for randomness in wireless opportunistic routing Proceedings of ACM SIGCOMM 2007 169 180Kohler E Handley M Floyd S Datagram Congestion Control Protocol (DCCP), IETF RFC 4340 2006 http://www.rfc-editor.org/rfc/rfc4340.txtSchierl, T., Ganger, K., Hellge, C., Wiegand, T., & Stockhammer, T. (2006). SVC-based multisource streaming for robust video transmission in mobile ad hoc networks. IEEE Wireless Communications, 13(5), 96-103. doi:10.1109/wc-m.2006.250365Iera, A., Molinaro, A., Paratore, S. Y., Ruggeri, G., & Zurzolo, A. (2011). Making a mesh router/gateway from a smartphone: Is that a practical solution? Ad Hoc Networks, 9(8), 1414-1429. doi:10.1016/j.adhoc.2011.03.00

A system architecture and implementation for meshed multicast in MANET using SIP

Mobile Ad-Hoc Network (MANET) is an active topic of research for its potential of providing pervasive services anywhere and anytime, even though some challenges need to be handled first. In contrast to conventional networks, ad hoc networks are formed by a set of devices that communicate without using a pre-existing network infrastructure. Multicast is an efficient transmission scheme for supporting group communication in networks. The concept of overlay networks enables multicast to be deployed as a service network rather than a network primitive mechanism, allowing deployment over heterogeneous networks without the need of universal network support. In this thesis, we propose an overlay multicast framework to handle multicasts in MANET environment in a flexible way. Our approach is using SIP to discover peers to set up a meshed overlay network first, then overlay multicast trees are set up on demand. To cope with the bandwidth limitation problem, the Dominating Set Based and Multi-Recipient routing are adopted, so that the virtual meshed network topology gradually adopts the changes in the underlying network in a distributed manner and the multicast tree is adapted to the updated topology information accordingly. A prototype is built to evaluate the feasibility and performance of the proposed framework

Dynamic services in mobile ad hoc networks

The increasing diffusion of wireless-enabled portable devices is pushing toward the design of novel service scenarios, promoting temporary and opportunistic interactions in infrastructure-less environments. Mobile Ad Hoc Networks (MANET) are the general model of these higly dynamic networks that can be specialized, depending on application cases, in more specific and refined models such as Vehicular Ad Hoc Networks and Wireless Sensor Networks. Two interesting deployment cases are of increasing relevance: resource diffusion among users equipped with portable devices, such as laptops, smart phones or PDAs in crowded areas (termed dense MANET) and dissemination/indexing of monitoring information collected in Vehicular Sensor Networks. The extreme dynamicity of these scenarios calls for novel distributed protocols and services facilitating application development. To this aim we have designed middleware solutions supporting these challenging tasks. REDMAN manages, retrieves, and disseminates replicas of software resources in dense MANET; it implements novel lightweight protocols to maintain a desired replication degree despite participants mobility, and efficiently perform resource retrieval. REDMAN exploits the high-density assumption to achieve scalability and limited network overhead. Sensed data gathering and distributed indexing in Vehicular Networks raise similar issues: we propose a specific middleware support, called MobEyes, exploiting node mobility to opportunistically diffuse data summaries among neighbor vehicles. MobEyes creates a low-cost opportunistic distributed index to query the distributed storage and to determine the location of needed information. Extensive validation and testing of REDMAN and MobEyes prove the effectiveness of our original solutions in limiting communication overhead while maintaining the required accuracy of replication degree and indexing completeness, and demonstrates the feasibility of the middleware approach

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.Deploying a network of sensors to monitor an environment is a common practice. For example, cameras in museums, supermarkets, or buildings are installed for surveillance purposes. However, while a decade ago, most deployed sensor networks involved a limited number of sensors, wired to a central processing unit, nowadays, the focus is on wireless, distributed, sensing nodes. Sensor technology has greatly advanced in terms of size, power consumption, processing capabilities, and low cost, thus fostering deployments of self-organizing wireless sensor networks over large geographical areas. For example, sensor networks have been used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Yet, sensor networks are usually perceived as ``something'' remote in the forest or on the battlefield, and regular users do not yet benefit from them. With the ubiquity and ever-increasing capabilities of mobile devices, such as smart phones and computers embedded in cars, urban environments offer the elements necessary to create people-centric mobile sensor networks and support a large variety of so-called sensing applications ranging from emergency and surveillance to tourist guidance and entertainment. For example, near-ubiquitous smart phones with audio and video sensing capabilities and more sensors in the near future can be used to provide shopping recommender services to inform users of special offers at the mall. Sensor-equipped cars can be used to provide traffic information services to alert drivers to upcoming traffic jams. However, urban mobile sensor networks are challenging programming environments due to the dynamism of mobile devices, the resource constraints of battery-powered devices, the software and hardware heterogeneity, and the large number of concurrent applications that they need to support. These requirements hinder the direct adoption of traditional distributed computing platforms developed for static resource-rich networks. This dissertation presents two architectures that can support the development of mobile sensing applications in urban environments. Contory offers a declarative programming model that views the urban network as a distributed sensor database. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption. The proposed architectures offer many opportunities to flexibly and quickly establish customized services that can greatly enhance the users' urban experience. Further steps to fully accomplish people-centric mobile sensing applications will have to address more technical issues as well as social and legal concerns

Using Aerial and Vehicular NFV Infrastructures to Agilely Create Vertical Services

5G communications have become an enabler for the creation of new and more complex networking scenarios, bringing together different vertical ecosystems. Such behavior has been fostered by the network function virtualization (NFV) concept, where the orchestration and virtualization capabilities allow the possibility of dynamically supplying network resources according to its needs. Nevertheless, the integration and performance of heterogeneous network environments, each one supported by a different provider, and with specific characteristics and requirements, in a single NFV framework is not straightforward. In this work we propose an NFV-based framework capable of supporting the flexible, cost-effective deployment of vertical services, through the integration of two distinguished mobile environments and their networks: small sized unmanned aerial vehicles (SUAVs), supporting a flying ad hoc network (FANET) and vehicles, promoting a vehicular ad hoc network (VANET). In this context, a use case involving the public safety vertical will be used as an illustrative example to showcase the potential of this framework. This work also includes the technical implementation details of the framework proposed, allowing to analyse and discuss the delays on the network services deployment process. The results show that the deployment times can be significantly reduced through a distributed VNF configuration function based on the publish&-subscribe model.This article has been partially supported by the European H2020 5GinFIRE project (grant agreement 732497). The work of the Universidad Carlos III team members was partially supported by the European H2020 LABYRINTH project (grant agreement H2020-MG-2019-TwoStages-861696), and by the TRUE5G project (PID2019-108713RB-C52PID2019-108713RB-C52/AEI/10.13039/501100011033) funded by the Spanish National Research Agency; and the work of the Instituto de Telecomunicações team members, by the Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 framework Mobilizer Project 5G with Nr. 024539 (POCI-01-0247-FEDER-024539)

A QoS-Based Wireless Multimedia Sensor Cluster Protocol

Wireless Sensor Networks (WSNs) provide a wireless network infrastructure for sensed data transport in environments where wired or satellite technologies cannot be used. Because the embedded hardware of the sensor nodes has been improved very much in the last years and the number of real deployments is increasing considerably, they have become a reliable option for the transmission of any type of sensed data, from few sensed measures to multimedia data. This paper proposes a new protocol that uses an ad hoc cluster based architecture which is able to adapt the logical sensor network topology to the delivered multimedia stream features, guaranteeing the quality of the communications. The proposed protocol uses the quality of service (QoS) parameters, such as bandwidth, delay, jitter, and packet loss, of each type of multimedia stream as a basis for the sensor clusters creation and organization inside the WSN, providing end-to-end QoS for each multimedia stream. We present real experiments that show the performance of the protocol for several video and audio cases when it is runningThis work has been partially supported by the "Ministerio de Ciencia e Innovacion," through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental," Project TEC2011-27516. This work has also been partially supported by the Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, by the Government of Russian Federation, Grant 074-U01, and by National Funding from the Fundacao para a Ciencia e a Tecnologia (FCT) through the PEst-OE/EEI/LA0008/2013 Project.Díaz Santos, JR.; Lloret, J.; Jimenez, JM.; Rodrigues, JJPC. (2014). A QoS-Based Wireless Multimedia Sensor Cluster Protocol. International Journal of Distributed Sensor Networks. 2014:1-17. https://doi.org/10.1155/2014/480372S1172014Bri, D., Garcia, M., Lloret, J., & Dini, P. (2009). Real Deployments of Wireless Sensor Networks. 2009 Third International Conference on Sensor Technologies and Applications. doi:10.1109/sensorcomm.2009.69Karim, L., Anpalagan, A., Nasser, N., & Almhana, J. (2013). Sensor-based M2M Agriculture Monitoring Systems for Developing Countries: State and Challenges. Network Protocols and Algorithms, 5(3), 68. doi:10.5296/npa.v5i3.3787Edo, M., Canovas, A., Garcia, M., & Lloret, J. (s. f.). Providing VoIP and IPTV Services in WLANs. Handbook of Research on Mobility and Computing, 426-444. doi:10.4018/978-1-60960-042-6.ch028Diab, R., Chalhoub, G., & Misson, M. (2013). Overview on Multi-Channel Communications in Wireless Sensor Networks. Network Protocols and Algorithms, 5(3), 112. doi:10.5296/npa.v5i3.3811Khoukhi, L., & Cherkaoui, S. (2010). Intelligent QoS management for multimedia services support in wireless mobile ad hoc networks. Computer Networks, 54(10), 1692-1706. doi:10.1016/j.comnet.2010.01.014Abbas, C. J. B., Orozco, A. L. S., & Villalba, L. J. G. (2012). A distributed QoS mechanism for ad hoc network. International Journal of Ad Hoc and Ubiquitous Computing, 11(1), 25. doi:10.1504/ijahuc.2012.049282Çevik, T., & Zaim, A. H. (2013). A Multichannel Cross-Layer Architecture for Multimedia Sensor Networks. International Journal of Distributed Sensor Networks, 9(3), 457045. doi:10.1155/2013/457045Li, Z., Bi, J., & Chen, S. (2013). Traffic Prediction-Based Fast Rerouting Algorithm for Wireless Multimedia Sensor Networks. International Journal of Distributed Sensor Networks, 9(5), 176293. doi:10.1155/2013/176293Lloret, J., Palau, C., Boronat, F., & Tomas, J. (2008). Improving networks using group-based topologies. Computer Communications, 31(14), 3438-3450. doi:10.1016/j.comcom.2008.05.030Lloret, J., Garcia, M., Tomás, J., & Boronat, F. (2008). GBP-WAHSN: A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks. Journal of Computer Science and Technology, 23(3), 461-480. doi:10.1007/s11390-008-9147-6Lehsaini, M., Guyennet, H., & Feham, M. (2010). An efficient cluster-based self-organisation algorithm for wireless sensor networks. International Journal of Sensor Networks, 7(1/2), 85. doi:10.1504/ijsnet.2010.031852Lloret, J., Garcia, M., Bri, D., & Diaz, J. (2009). A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks. Sensors, 9(12), 10513-10544. doi:10.3390/s91210513Diaz, J. R., Lloret, J., Jimenez, J. M., & Sendra, S. (2014). MWAHCA: A Multimedia Wireless Ad Hoc Cluster Architecture. The Scientific World Journal, 2014, 1-14. doi:10.1155/2014/913046Wei, D., & Chan, H. (2006). Clustering Ad Hoc Networks: Schemes and Classifications. 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks. doi:10.1109/sahcn.2006.288583Yu, J. Y., & Chong, P. H. J. (2005). A survey of clustering schemes for mobile ad hoc networks. IEEE Communications Surveys & Tutorials, 7(1), 32-48. doi:10.1109/comst.2005.1423333Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14-15), 2826-2841. doi:10.1016/j.comcom.2007.05.024Boyinbode, O., Le, H., & Takizawa, M. (2011). A survey on clustering algorithms for wireless sensor networks. International Journal of Space-Based and Situated Computing, 1(2/3), 130. doi:10.1504/ijssc.2011.040339Ramachandran, L., Kapoor, M., Sarkar, A., & Aggarwal, A. (2000). Clustering algorithms for wireless ad hoc networks. Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications - DIALM ’00. doi:10.1145/345848.345860Chatterjee, M., Das, S. K., & Turgut, D. (2002). Cluster Computing, 5(2), 193-204. doi:10.1023/a:1013941929408Huang, Y.-M., Hsieh, M.-Y., & Wang, M.-S. (2007). Reliable transmission of multimedia streaming using a connection prediction scheme in cluster-based ad hoc networks. Computer Communications, 30(2), 440-452. doi:10.1016/j.comcom.2006.09.012Tang, S., & Li, W. (2006). QoS supporting and optimal energy allocation for a cluster based wireless sensor network. Computer Communications, 29(13-14), 2569-2577. doi:10.1016/j.comcom.2006.02.007Rosário, D., Costa, R., Paraense, H., Machado, K., Cerqueira, E., Braun, T., & Zhao, Z. (2012). A Hierarchical Multi-hop Multimedia Routing Protocol for Wireless Multimedia Sensor Networks. Network Protocols and Algorithms, 4(4). doi:10.5296/npa.v4i4.2121Diaz, J. R., Lloret, J., Jiménez, J. M., & Hammoumi, M. (2014). A new multimedia-oriented architecture and protocol for wireless ad hoc networks. International Journal of Ad Hoc and Ubiquitous Computing, 16(1), 14. doi:10.1504/ijahuc.2014.062486Meghanathan, N., & Mumford, P. (2013). Centralized and Distributed Algorithms for Stability-based Data Gathering in Mobile Sensor Networks. Network Protocols and Algorithms, 84. doi:10.5296/npa.v5i4.420

Voice Service Support in Mobile Ad Hoc Networks

Mobile ad hoc networks are expected to support voice traffic. The requirement for small delay and jitter of voice traffic poses a significant challenge for medium access control (MAC) in such networks. User mobility makes it more complex due to the associated dynamic path attenuation. In this paper, a MAC scheme for mobile ad hoc networks supporting voice traffic is proposed. With the aid of a low-power probe prior to DATA transmissions, resource reservation is achieved in a distributed manner, thus leading to small delay and jitter. The proposed scheme can automatically adapt to dynamic path attenuation in a mobile environment. Simulation results demonstrate the effectiveness of the proposed scheme.Comment: To appear in the Proceedings of the IEEE Global Communications Conference (GLOBECOM), Washington, DC, November 26 - 30, 200

GRIDKIT: Pluggable overlay networks for Grid computing

A `second generation' approach to the provision of Grid middleware is now emerging which is built on service-oriented architecture and web services standards and technologies. However, advanced Grid applications have significant demands that are not addressed by present-day web services platforms. As one prime example, current platforms do not support the rich diversity of communication `interaction types' that are demanded by advanced applications (e.g. publish-subscribe, media streaming, peer-to-peer interaction). In the paper we describe the Gridkit middleware which augments the basic service-oriented architecture to address this particular deficiency. We particularly focus on the communications infrastructure support required to support multiple interaction types in a unified, principled and extensible manner-which we present in terms of the novel concept of pluggable overlay networks