Currently, NDN-based VANETs protocols have several problems with packet overhead of rebroadcasting, control packet, and the accuracy of next-hop selection due to the dynamic topology. To deal with these problems in this paper, we propose a robust and lightweight forwarding protocol in Vehicular ad-hoc Named Data Networking. The concept of our forwarding protocol is adopting a packet-free approach. A vehicle collects its neighbor's visual identification by a pair of cameras (front and rear) to assign a unique visual ID for each node. Based on these IDs, we construct a hop-by-hop FIB-based forwarding strategy effectively. Furthermore, the Face duplication [1] in the wireless environment causes an all-broadcast problem. We add the visual information to Face to distinguish the incoming and outgoing Face to prevent broadcast-storm and make FIB and PIT work more accurate and efficiently. The performance evaluation results focusing on the communication overhead show that our proposal has better results in overall network traffic costs and Interest satisfaction ratio than previous works.

Software-defined networking (SDN) decouples the control and forwarding of network devices, providing benefits such as simplified control. However, due to cost constraints and other factors, SDN is difficult to fully deploy. It has been proposed that SDN devices can be incrementally deployed in a traditional IP network, i.e., hybrid SDN, to provide partial SDN benefits. Studies have shown that better traffic engineering performance can be achieved by modifying the coverage and placement of SDN devices in hybrid SDN, because they can influence the behavior of legacy switches through certain strategies. However, it is difficult to develop and execute a traffic engineering strategy in hybrid SDN. This article proposes a routing algorithm to achieve approximate load balancing, which minimizes the maximum link utilization by using the optimal solution of linear programming and merging the minimum split traffic flows. A multipath forwarding mechanism under the same problem is designed to optimize transmission time. Experiments show that our algorithm has certain advantages in link utilization and transmission time compared to traditional distributed routing algorithms like OSPF and some hybrid SDN routing mechanisms. Furthermore, our algorithm can approximate the control effect of full SDN when the deployment rate of SDN devices is 40%.

In this article, we propose a method to identify the link layer home network topology, motivated by applications to cost reduction of support centers. If the topology of home networks can be identified automatically and efficiently, it is easier for operators of support centers to identify fault points. We use MAC address forwarding tables (AFTs) which can be collected from network devices. There are a couple of existing methods for identifying a network topology using AFTs, but they are insufficient for our purpose; they are not applicable to some specific network topologies that are typical in home networks. The advantage of our method is that it can handle such topologies. We also implemented these three methods and compared their running times. The result showed that, despite its wide applicability, our method is the fastest among the three.

In wireless multi-hop networks such as ad hoc networks and sensor networks, backoff-based opportunistic routing protocols, which make a forwarding decision based on backoff time, have been proposed. In the protocols, each potential forwarder calculates the backoff time based on the product of a weight and global scaling factor. The weight prioritizes potential forwarders and is calculated based on hop counts to the destination of a sender and receiver. The global scaling factor is a predetermined value to map the weight to the actual backoff time. However, there are three common issues derived from the global scaling factor. First, it is necessary to share the predetermined global scaling factor with a centralized manner among all terminals properly for the backoff time calculation. Second, it is almost impossible to change the global scaling factor during the networks are being used. Third, it is difficult to set the global scaling factor to an appropriate value since the value differs among each local surrounding of forwarders. To address the aforementioned issues, this paper proposes a novel decentralized local scaling factor control without relying on a predetermined global scaling factor. The proposed method consists of the following three mechanisms: (1) sender-centric local scaling factor setting mechanism in a decentralized manner instead of the global scaling factor, (2) adaptive scaling factor control mechanism which adapts the local scaling factor to each local surrounding of forwarders, and (3) mitigation mechanism for excessive local scaling factor increases for the local scaling factor convergence. Finally, this paper evaluates the backoff-based opportunistic routing protocol with and without the proposed method using computer simulations.

The periodic disaster backup activity among geographically distributed multiple datacenters consumes huge network resources and therefore imposes a heavy burden on datacenters and transmission links. Previous work aims at least completion time, maximum utility or minimal cost, without consideration of load balance for limited network resources, likely to result in unfair distribution of backup load or significant impact on daily network services. In this paper, we propose a new progressive forwarding disaster backup strategy in the Software Defined Network scenarios to mitigate forwarding burdens on source datacenters and balance backup loads on backup datacenters and transmission links. We construct a new redundancy-aware time-expanded network model to divide time slots according to redundancy requirement, and propose role-switching method over time to utilize forwarding capability of backup datacenters. In every time slot, we leverage two-step optimization algorithm to realize capacity-constrained backup datacenter selection and fair backup load distribution. Simulations results prove that our strategy achieves good performance in load balance under the condition of guaranteeing transmission completion and backup redundancy.

Location-based forwarding is a key driver for location-based services. This paper designs forwarding information data structures for location-based forwarding in Internet Service Provider (ISP) scale networks based on Named Data Networking (NDN). Its important feature is a naming scheme which represents locations by leveraging space-filling curves.

In the 5G era, centralized mobility management raises the issue of traffic concentration on the mobility anchor. Distributed mobility management is expected to be a solution for this issue, as it moves mobility anchor functions to multiple edge routers. However, it incurs path stretch and redundant traffic on the backhaul links. Although these issues were not considered important in the 3G/4G era, they are expected to be a serious problem in the 5G era. In this paper, we design a routing-based mobility management mechanism to address the above problems. The mechanism integrates distributed routing with Bloom Filters and an anchor-less scheme where edge routers work as mobility anchors. Simulations show that the proposed mechanism achieves a good balance between redundant traffic on the backhaul links and routing overhead.

In this paper, a multi-data and multi-ACK verified selective forwarding attacks (SFAs) detection scheme is proposed for containing SFAs. In our scheme, each node (in addition to the nodes in the hotspots area) generates multiple acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. In multiple ACK message, one ACK is returned along the data forwarding path, other ACKs are returned along different routing paths, and thus malicious nodes can be located accurately. At the same time, source node send multiple data routing, one is primary data routing, the others are backup data routing. Primary data is routed to sink directly, but backup data is routed to nodes far from sink, and then waits for the returned ACK of sink when primary data is routed to sink. If a node doesn't receive the ACK, the backup data is routed to sink, thus the success rate of data transmission and lifetime can be improved. For this case, the MDMA scheme has better potential to detect abnormal packet loss and identify suspect nodes as well as resilience against attack. Theoretical analysis and experiments show that MDMA scheme has better ability for ensuring success rate of data transmission, detecting SFA and identifying malicious nodes.

In this paper, we investigate multi-service forwarding in selfish wireless networks (SeWN) with selfish relay nodes (RN). The RN's node-selfishness is characterized from the perspectives of its residual energy and the incentive paid by the source, by which the degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) are defined. Meanwhile, a framework of the node-selfishness management is conceived to extract the RNs' node-selfishness information (NSI). Based on the RN's NSI, the expected energy cost and expected service profit are determined for analyzing the effect of the RN's node-selfishness on the multi-service forwarding. Moreover, the optimal incentive paid by the source is obtained for minimizing its cost and, at the same time, effectively stimulating the multi-service delivery. Simulation validate our analysis.

The growth of the size of the routing tables limits the scalability of the conventional IP routing. As scalable routing schemes for large-scale networks are highly demanded, this paper proposes and evaluates an efficient geometric routing scheme and related low-cost node design applicable to large-scale networks. The approach guarantees that greedy forwarding on derived coordinates will result in successful packet delivery to every destination in the network by relying on coordinates deduced from a spanning tree of the network. The efficiency of the proposed scheme is measured in terms of routing quality (stretch) and size of the coordinates. The cost of the proposed router is quantified in terms of area complexity of the hardware design and all the evaluations involve comparison with a state-of-the-art approach with virtual coordinates in the hyperbolic plane. Extensive simulations assess the proposal in large topologies consisting of up to 100K nodes. Experiments show that the scheme has stretch properties comparable to geometric routing in the hyperbolic plane, while enabling a more efficient hardware design, and scaling considerably better in terms of storage requirements for coordinate representation. These attractive properties make the scheme promising for routing in large networks.

Content-Centric Networking (CCN) employs a hierarchical but location independent content naming scheme. While such a location independent naming brings various benefits including efficient content delivery, mobility, and multihoming, location independent name prefixes are hard to aggregate. This poses a serious scaling issue on the efficiency of looking up content names in a huge Forwarding Information Base (FIB) by longest prefix matching, which requires seeking the longest matching prefix through all candidate prefix lengths. We propose a new scheme for efficiently looking up non-aggregatable name prefixes in a large FIB. The proposed scheme is based on the observation that the bottleneck of FIB lookup is the random accesses to the high-latency off-chip DRAM for prefix seeking and this can be reduced by exploiting the information on the longest matching prefix length in the previous hop. Our evaluation results show that the proposed scheme significantly improves FIB lookup latency with a reasonable traffic parameters observed in today's Internet.

Recently, many kinds of content are being circulated within a great many service-specific overlay networks. When the content is not extremely delay-sensitive, content circulation between wireless terminals can be realized without additional resources by using off-peak periods in wireless access links. In such content circulation, peer-to-peer content multicast is a promising approach to reduce the load on the centralized server. However, to minimize battery drain, each wireless terminal can only forward content to a restricted number of neighboring terminals once it has received the content. This paper proposes an efficient forwarding scheme for peer-to-peer content multicast between the wireless terminals intermittently connected with the backhaul network. In the proposed scheme, a restricted number of terminals with an earlier start time of off-peak periods are selected to forward the content when the number of forwarding hops from the source terminal is less than or equal to a predetermined threshold. In contrast, a restricted number of terminals are selected randomly when the number of forwarding hops exceeds the threshold. This paper clarifies that the proposed hybrid forwarding scheme can multicast the content to many terminals within an arbitrarily restricted period. A guideline to determine the optimum threshold for switching the terminal selection method in the proposed hybrid scheme is derived from simulation results.

Existing forwarding strategies for delay tolerant networks aim at network throughput maximization. They provide forwarding opportunities to more reachable destinations. This results in the long end-to-end delay and low throughput of less reachable destinations. In this paper, we propose two forwarding strategies to improve the throughput of less reachable nodes with little throughput degradation of more reachable nodes. Evaluation results show that the proposed forwarding strategies can control the levels of fairness among the destinations while maintaining high throughput, compared with the legacy forwarding strategies.

High-speed IP address lookup with fast prefix update is essential for designing wire-speed packet forwarding routers. The developments of optical fiber and 100 Gbps interface technologies have placed IP address lookup as the major bottleneck of high performance networks. In this paper, we propose a novel structure named Compressed Multi-way Prefix Tree (CMPT) based on B+ tree to perform dynamic and scalable high-speed IP address lookup. Our contributions are to design a practical structure for high-speed IP address lookup suitable for both IPv4 and IPv6 addresses, and to develop efficient algorithms for dynamic prefix insertion and deletion. By investigating the relationships among routing prefixes, we arrange independent prefixes as the search indexes on internal nodes of CMPT, and by leveraging a nested prefix compression technique, we encode all the routing prefixes on the leaf nodes. For any IP address, the longest prefix matching can be made at leaf nodes without backtracking. For a forwarding table with u independent prefixes, CMPT requires O(logmu) search time and O(mlogmu) dynamic insert and delete time. Performance evaluations using real life IPv4 forwarding tables show promising gains in lookup and dynamic update speeds compared with the existing B-tree structures.

Intermittent Periodic Transmission (IPT forwarding) has been proposed as an efficient packet relay method for wireless backhaul. In IPT forwarding, a source node sends packets to a destination node with a certain time interval (IPT duration) so that signal interference between relay nodes that send packets simultaneously are reduced and frequency reuse is realized which brings about an improvement of system throughput. However, optimum IPT duration setting for each node is a difficult problem which is not solved adequately yet. In this paper, we propose a new IPT duration setting protocol which employs some training packets to search for the optimum IPT duration for each node. A simulation and experiment show that the proposed method is not only very effective but also practical for wireless backhaul.

In this letter, we discuss a forwarding method for maximizing network lifetime, which combines multi-hop forwarding and direct forwarding with a direct/multi-hop forwarding ratio of each sensor node. The direct forwarding ratio refers to the forwarding amount ratio of sensor nodes' own data directly towards a sink node in one packet/instance data generation rate. We tackle an optimization problem to determine the direct forwarding ratio of each sensor node, maximizing network lifetime, as well as nearly guaranteeing energy consumption balancing characteristics. The optimization problem is tackled through the Lagrange multiplier approach. We found that the direct forwarding ratio is overall inversely proportional to the increase of node index in h < i ≤ N case. Finally, we compare energy consumption and network lifetime of the proposed forwarding method with other existing forwarding methods. The numerical results show that the proposed forwarding method balances energy consumption in most of the sensor nodes, comparing with other existing forwarding methods, such as multi-hop forwarding and direct forwarding. The proposed forwarding method also maximizes network lifetime.

In this letter, we propose three algorithms to reduce congestion for greedy forwarding, which is one of common principles in geographic routing. The new algorithms take geographic position information and network congestion metrics to balance traffic. When these algorithms are combined with well-known GPSR protocol [1], packet delivery ratio is enhanced by reducing number of lost packets in a buffer. In addition, end-to-end delay is reduced by bypassing congested nodes. These features are evaluated and analyzed through several simulation results.

In delay tolerant networks, energy efficient forwarding algorithms are significant to enhance the performance of message transmission probability. In this paper, we focus on the problem of optimal probabilistic epidemic forwarding with energy constraint. By introducing a continuous time model, we obtain the optimal static and dynamic policies for multi-messages forwarding. Extensive numerical results show that the optimal dynamic policy achieves higher transmission probability than the optimal static policy while the number of messages decreases the average transmission probability.

Packet classification has become one of the most important application techniques in network security since the last decade. The technique involves a traffic descriptor or user-defined criteria to categorize packets to a specific forwarding class which will be accessible for future security handling. To achieve fast packet classification, we propose a new scheme, Hierarchical Cross-Producting. This approach simplifies the classification procedure and decreases the distinct combinations of fields by hierarchically decomposing the multi-dimensional space based on the concept of telescopic search. Analogous to the use of telescopes with different powers**, a multiple-step process is used to search for targets. In our scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into recursive searching for matching subspaces. The required storage of our scheme could be significantly reduced since the distinct field specifications of subspaces is manageable. The performance are evaluated based on both real and synthetic filter databases. The experimental results demonstrate the effectiveness and scalability of the proposed scheme.

In the last decade, the technique of packet classification has been widely deployed in various network devices, including routers, firewalls and network intrusion detection systems. In this work, we improve the performance of packet classification by using multiple hash tables. The existing hash-based algorithms have superior scalability with respect to the required space; however, their search performance may not be comparable to other algorithms. To improve the search performance, we propose a tuple reordering algorithm to minimize the number of accessed hash tables with the aid of bitmaps. We also use pre-computation to ensure the accuracy of our search procedure. Performance evaluation based on both real and synthetic filter databases shows that our scheme is effective and scalable and the pre-computation cost is moderate.