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As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence of routing protocols after a network failure becomes a growing problem. To assure fast recovery from link and node failures in IP networks, we present a new recovery scheme called Multiple Routing Configurations (MRC). MRC is based on keeping additional routing information in the routers, and allows packet forwarding to continue on an alternative output link immediately after the detection of a failure. Our proposed scheme guarantees recovery in all single failure scenarios, using a single mechanism to handle both link and node failures, and without knowing the root cause of the failure. MRC is strictly connectionless, and assumes only destination based hop-by-hop forwarding. It can be implemented with only minor changes to existing solutions. In this paper we present MRC, and analyze its performance with respect to scalability, backup path lengths, and load distribution after a failure. I. INTRODUCTIONIn recent years the Internet has been transformed from a special purpose network to an ubiquitous platform for a wide range of everyday communication services. The demands on Internet reliability and availability have increased accordingly. A disruption of a link in central parts of a network has the potential to affect hundreds of thousands of phone conversations or TCP connections, with obvious adverse effects.The ability to recover from failures has always been a central design goal in the Internet [1]. IP networks are intrinsically robust, since IGP routing protocols like OSPF are designed to update the forwarding information based on the changed topology after a failure. This re-convergence assumes full distribution of the new link state to all routers in the network domain. When the new state information is distributed, each router individually calculates new valid routing tables.This network-wide IP re-convergence is a time consuming process, and a link or node failure is typically followed by a period of routing instability. During this period, packets may be dropped due to invalid routes. This phenomenon has been studied in both IGP [2] and BGP context [3], and has an adverse effect on real-time applications [4]. Events leading to a re-convergence have been shown to occur frequently, and are often triggered by external routing protocols [5].Much effort has been devoted to optimizing the different steps of the convergence of IP routing, i.e., detection, dissemination of information and shortest path calculation, but the convergence time is still too large for applications with real time demands [6]. A key problem is that since most network

In the era of Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then, we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.Rong Yu [S05, M08] (yurong@ieee.org) received his Ph.D. from Tsinghua University, China, in 2007. After that, he worked in the School of Electronic and Information Engineering of South China University of Technology (SCUT). In 2010, he joined the Institute of Intelligent Information Processing at Guangdong University of Technology (GDUT), where he is now an associate professor. His research interest mainly focuses on wireless communications and networking, including cognitive radio, wireless sensor networks, and home networking. He is the co-inventor of over 10 patents and author or co-author of over 50 international journal and conference papers. Dr. Yu is currently serving as the deputy secretary general of the Internet of Things (IoT) Industry Alliance, Guangdong, China, and the deputy head of the IoT Engineering Center, Guangdong, China. He is the member of home networking standard committee in China, where he leads the standardization work of three standards. 9 Yan Zhang [SM10] (yanzhang@ieee.org) received a Ph.D. degree from Nanyang Technological University, Singapore. He is working with Simula Research Laboratory, Norway; and he is an adjunct Associate Professor at the University of Oslo, Norway. He is an associate editor or guest editor of a number of international journals. He serves as organizing committee chairs for many international conferences. His research interests include resource, mobility, spectrum, energy, and data management in wireless communications and networking. and the Head of the Network Convergence Laboratory (NCL) in Essex. His main research interests include wireless networks/communications, fixed mobile convergence, future Internet technology and network virtualization. He has published over 150 papers in the above research areas. He serves on the editorial boards of both IEEE and non-IEEE journals. He is a Senior Member of IEEE and a Fellow of IET.

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