Forwarding Decisions Research Articles

Centralization of Network Using Openflow Protocol

Traditional network is used have distributed nature which face complexities while modifying, monitoring, securing the network. The centralization of network is proving very effective in terms for management, implementation of new applications, monitoring the network. The programmable network using programmable devices helps to implement centralization of network successfully. To reduce the latency in the network the control parameters of control plane are used for making the forwarding decision by the centralized controller. Software Defined Network (SDN) is emerging technology having the centralized policy to design cloud network topology. The abstraction of control plane from data plane is isolating the control parameters from the flow of packets for making an efficient forwarding decision by programmable device. This device is known to be controller; it also reduces the complexities to process the data overhead. The OpenFlow protocol is used for abstraction and transferring the control parameters over secure channel. The protocol enables the enterprise to design well managed and secure cloud. In this paper, the experimental test bed is built which provides the centralized System Center Virtual Machine Manager (SCVMM) controller in the private cloud. The cloud provides its virtual Platform as a Service (PaaS) to the client by creating multiple Virtual Machine instances on single machine. The Virtual Private Network is created by using the Network Virtualization Generic Routing (NVGRE) tunnelling Protocol for the client to reach up to the hosted platform.

TMC: Exploiting Trajectories for Multicast in Sparse Vehicular Networks

Multicast is a crucial routine operation for vehicular networks, which underpins important functions such as message dissemination and group coordination. As vehicles may distribute over a vast area, the number of vehicles in a given region can be limited which results in sparse node distribution in part of the vehicular network. This poses several great challenges for efficient multicast, such as network disconnection, scarce communication opportunities and mobility uncertainty. Existing multicast schemes proposed for vehicular networks typically maintain a forwarding structure assuming the vehicles have a high density and move at low speed while these assumptions are often invalid in a practical vehicular network. As more and more vehicles are equipped with GPS enabled navigation systems, the trajectories of vehicles are becoming increasingly available. In this work, we propose an approach called TMC to exploit vehicle trajectories for efficient multicast in vehicular networks. The novelty of TMC includes a message forwarding metric that characterizes the capability of a vehicle to forward a given message to destination nodes, and a method of predicting the chance of inter-vehicle encounter between two vehicles based only on their trajectories without accurate timing information. TMC is designed to be a distributed approach. Vehicles make message forwarding decisions based on vehicle trajectories shared through inter-vehicle exchanges without the need of central information management. We have performed extensive simulations based on real vehicular GPS traces and compared our proposed TMC scheme with other existing approaches. The performance results demonstrate that our approach can achieve a delivery ratio close to that of the flooding-based approach while the cost is reduced by over 80 percent.

Using Stationary Relay Nodes (Thrown Boxes) to Maximize Message Forwarding Performance in Delay-Tolerant Networks

This paper addresses the efficiency on message forwarding over heterogeneous nodes in DTNs. Among the approaches for routing protocols in DTNs, the strategy of deploying the stationary relay nodes called ＂thrown boxes＂ is considered for increasing network performance efficiently. Till now, few studies have provided routing solutions for thrown-box-based network paradigms in the DTN research field. The technical content of this paper includes three parts. Firstly, this study considers the deployment of thrown boxes that can assist in message delivery in delay-tolerant networks. A utility-based algorithm is applied to make the message forwarding decision between two nodes whenever they are in contact. Secondly, we study where to appropriately deploy thrown boxes under various scenarios. Finally, this study runs simulations to evaluate the proposed scheme in terms of message delivery probability. Performance results show that the proposed algorithm achieves high performances and thrown boxes play an important role in message forwarding performance.

Opportunistic Flooding in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links

Flooding service has been investigated extensively in wireless networks to efficiently disseminate network-wide commands, configurations, and code binaries. However, little work has been done on low-duty-cycle wireless sensor networks in which nodes stay asleep most of the time and wake up asynchronously. In this type of network, a broadcasting packet is rarely received by multiple nodes simultaneously, a unique constraining feature that makes existing solutions unsuitable. In this paper, we introduce Opportunistic Flooding, a novel design tailored for low-duty-cycle networks with unreliable wireless links and predetermined working schedules. Starting with an energy-optimal tree structure, probabilistic forwarding decisions are made at each sender based on the delay distribution of next-hop receivers. Only opportunistically early packets are forwarded via links outside the tree to reduce the flooding delay and redundancy in transmission. We further propose a forwarder selection method to alleviate the hidden terminal problem and a link-quality-based backoff method to resolve simultaneous forwarding operations. We show by extensive simulations and test-bed implementations that Opportunistic Flooding is close to the optimal performance achievable by oracle flooding designs. Compared with Improved Traditional Flooding, our design achieves significantly shorter flooding delay while consuming only 20-60% of the transmission energy.

Energy-efficient cache node placement using genetic algorithm in wireless sensor networks

Wireless sensor network (WSN) applications are required to report events and service queries with minimum delay and minimal energy consumption. The network lifetime of a WSN can be extended if the amount of communication in the network is reduced. We can achieve this by caching useful data closer to the requesting node. Caching successfully reduces data access latency and also the number of packet transmissions in the network, thereby increasing network lifetime. However, the important aspect of caching schemes is to identify nodes that can implement caching decisions and also place such cache nodes in a way that they can provide services to as many sensor nodes as possible in their vicinity. This has led to the study of optimal deployment of these cache nodes in a WSN. We carried out experiments to demonstrate the use of a multi-objective genetic algorithm (GA) for cache node placement in a WSN. In this paper, GA optimization aims to increase two parameters: sensors per cache in charge and field coverage. We also show that the GA successfully helps in selecting sensor nodes to implement caching and request forwarding decisions. Finally, we run the Scaled Power Community Index Cooperative Caching scheme (scaPCICC) on the optimized network and compare the delay and total number of overhead messages in the network. We conclude that by reducing the number of messages in the network and reducing the data access latency, the energy consumption of the network is reduced and network lifetime is increased. The experiments were run on MATLAB and ns2.

Multi-criteria Receiver Self-Election Scheme for Optimal Packet Forwarding in Vehicular Ad hoc Networks

In most of the existing geographical forwarding methods of Vehicular Ad hoc NETwork (VANET), a node periodically sends “hello” messages to determine the positional information of its direct neighbors. Each node stores and maintains more or less accurate information of its direct neighbors in a table. However, due to high mobility vehicles and traffic congestion the stored neighbors information is quickly outdated, failure notification increases significantly, and leading sub-optimal path. Furthermore, the transmission of periodic “hello” messages and table maintenance consume resources, which is not suitable for sensitive VANET. In this paper, we propose a geographical forwarding mechanism based on Multi-criteria Receiver Self- Election (MRSE) scheme to find best next hop without sending the periodic “hello” messages and maintaining neighbors information in the table. The selection of best next hop is based on the multi-criteria waiting function. In this function, the four key parameters including link life time, optimal distance from sender to receiver, optimal transmission range, and received power are determined to enable the next candidate node to make packet forwarding decisions. The simulation results show that the MRSE scheme performs up to 22% better in terms of packet delivery ratio as compared to some existing schemes. In terms of average delay, MRSE scheme performs best, with as much as 81% decrease compared to some existing schemes.

Flow caching for high entropy packet fields

Packet classification on general purpose CPUs remains expensive regardless of advances in classification algorithms. Unless the packet forwarding pipeline is both simple and static in function, fine-tuning the system for optimal forwarding is a time-consuming and brittle process. Network virtualization and network function virtualization value general purpose CPUs exactly for their flexibility: in such systems, a single x86 forwarding element does not implement a single, static classification step but a sequence of dynamically reconfigurable and potentially complex forwarding operations. This leaves a software developer looking for maximal packet forwarding throughput with few options besides flow caching. In this paper, we consider the problem of flow caching and more specifically, how to cache forwarding decisions that depend on packet fields with high entropy (and therefore, change often); to this end, we arrive at algorithms that allow us to efficiently compute near optimal flow cache entries spanning several transport connections, even if forwarding decisions depend on transport protocol headers.

Road traffic and geography topology based opportunistic routing for VANETs

The message delivery ratio and transmission delay is affected deeply by road traffic flow in vehicular ad hoc networks (VANETs). An opportunistic routing based on geography and road traffic flow for VANETs (ORRIS) was proposed. ORRIS leverages the knowledge of geography positions, motion vectors and road traffic flows. In order to estimate the traffic flow density, the history of encounter number of the vehicles in the opposite direction is considered in ORRIS. The forwarding decisions are made by distributed vehicles based on the geography topology and the road traffic flow. The real map based simulation results show that ORRIS has a better performance than other algorithms, especially when the road traffic is busy or the traffic flow rates have great differences between roads.

The Psychology Behind People's Decision to Forward Disaster-Related Tweets

During a disaster, information spreads through social media. Although information that can save lives exists in social media, it can be difficult to find because it is buried under a sea of unverified information. One challenge in improving the use of social media for disaster management is to facilitate the spread of actionable information that improves people’s well-being and at the same time reduce the spread of misinformation that confuses people and interferes with the discovery of useful information. To this end, we study the psychology of message forwarding in social media. Based on the understanding of the psychology, we develop recommendations for designing tools that augment the forwarding decisions of individuals such that useful information spreads in social media. Here, we present the results from analyzing the forwarding of tweets related to the disasters caused by the Great East Japan Earthquake in 2011. The results from questionnaires suggest that people will be more likely to share a disaster-related message in a social media environment when they perceive the message as more important, accurate, anxiety provoking, familiar, informative, and fluent. The implications of the results on improving the quality of information in social media during disaster response are discussed.

Empirical Studies of Bio-Inspired Self-Organized Secure Autonomous Routing Protocol

A wireless sensor network (WSN) depends on miniaturized wireless sensor nodes that are deployed to monitor physical phenomena by communicating with each other with limited resources. The major factor to be tackled in the WSN is the network lifetime. A recent WSN routing protocol defined as secure real-time load distribution (SRTLD) uses broadcast packets to perform neighbor discovery and calculation at every hop while transferring data packets. Thus, it has high energy consumption. The proposed novel biological inspired self-organized secure autonomous routing protocol (BIOSARP) enhances SRTLD with an autonomous routing mechanism. In the BIOSARP mechanism, an optimal forwarding decision is obtained using improved ant colony optimization (IACO). In IACO, the pheromone value/probability is computed based on the end-to-end delay, remaining battery power, and link quality metrics. The proposed BIOSARP has been designed to reduce the broadcast and packet overhead in order to minimize the delay, packet loss, and power consumption in the WSN. In this paper, we present the architecture, implementation, and detailed outdoor experimental testbed results of the proposed BIOSARP. These results show that BIOSARP outperforms energy and delay ants algorithm, improved energy-efficient ant-based routing, and SRTLD in simulations and as well as in real testbed experimentation. The empirical study confirmed that BIOSARP offers better performance and can be practically implemented in the WSN applications for structural and environmental monitoring or battlefield surveillance.

Energy Efficient Geographic Routing Robust Against Location Errors

Realistic geographic routing algorithms need to ensure quality of services in wireless sensor network applications while being resilient to the inherent localization errors of positioning algorithms. A number of solutions robust against location errors have been proposed in the literature and their design focuses either on a high throughput or on a balanced energy consumption. Ideally, both aspects need to be addressed by the same algorithm, but in most cases, the proposed routing techniques compromise between the two. The present work aims to minimize such a tradeoff and to facilitate a higher packet delivery ratio than similar geographic routing techniques, while still being energy efficient. This is achieved through a novel proposal entitled energy conditioned mean square error algorithm (ECMSE), which makes use of statistical assumptions of Gaussianly distributed location error and Ricianly distributed distances between sensor nodes. In addition, it makes use of an energy efficient feature, which includes information about the energy cost of the forwarding decision. By using a location-error-resilient and distance-based power metric, the ECMSE provides an improved performance in realistic simulations in comparison with other error-coping geographic routing algorithms.

동적 무선 인체 통신망의 에너지 효율과 신뢰성을 위한 토폴로지 인식 기반 패킷 크기 및 포워딩 비율 결정 방법

인체에 부착된 센서들의 위치는 인간의 신체적 활동에 따라 자주 이동된다. 이에 따른 노드 위치 이동과 비가시선상의 문제들은 무선 인체 통신망에서 핫 스팟과 에너지 효율, 그리고 신뢰적인 통신 성능에 영향을 미친다. 우리는 빈번히 변화하는 네트워크 토폴로지와 채널 조건을 고려한 포워딩을 결정하는 방법을 제안하였다. 본 논문에서는 각 노드의 라우팅 레벨에서 입, 출력 링크들의 비율에 근거하여 포워딩 비율과 패킷들의 크기를 제어한다. 또한 패킷 크기와 포워딩 비율 제어를 지원하는 격자 기반의 연결을 확장함으로써 네트워크 토폴로지를 견고하게 한다. 본 논문의 시뮬레이션은 이러한 접근들이 네트워크 수명을 48.2% 증가시키는 것뿐 아니라 약 6.08%의 패킷 전달율의 증가가 있음을 증명한다. 또한 핫 스팟 문제도 본 제안을 통해 해결된다. The sensors attached on/in a person are moved since human body frequency changes their activity, therefore in wireless body area networks, nodal mobility and non-line-of-sight condition will impact on performance of networks such as energy efficiency and reliable communication. We then proposed schemes which study on forwarding decisions against frequent change of topology and channel conditions to increase reliable connections and improve energy efficiency. In this work, we control the size of packets, forwarding rate based on ratio of input links and output links at each node. We also robust the network topology by extending the peer to peer IEEE 802.15.4-based. The adaptive topology from chain-based to grid-based can optimal our schemes. The simulation shows that these approaches are not only extending network lifetime to 48.2 percent but also increase around 6.08 percent the packet delivery ratio. The "hot spots" problem is also resolved with this approach.

Social Contribution-Based Routing Protocol for Vehicular Network with Selfish Nodes

Routing in vehicular network is a challenging task due to the characteristic of intermittent connectivity, especially when nodes behave selfishly in the real world. Previous works usually assume that all nodes in the network are willing to forward packets for others, which is impractical in real world. Selfish behaviors of nodes would degrade network performance greatly. In this paper, we propose SCR, a social contribution-based routing protocol, for selfish vehicular network. When making forwarding decision, SCR considers both the delivery probability to the destination and the social contributions of the relay node. The delivery probability is determined by the social relations among nodes and social contribution is used as the incentive to stimulate selfish nodes to be more cooperative, which consists of reciprocal contribution and community contribution. The node with higher delivery probability and lower social contributions is the preferred candidate for the next hop. Simulation results show that SCR achieves better performance than other social routing protocols with the incentive scheme.

Distributed energy-efficient estimation in spatially correlated wireless sensor networks

We study the problem of maximizing lifetime in sensor networks that are deployed for estimating an unknown parameter or process. Sensors take measurements and transport them in multi-hop fashion to a fusion center (FC) for Maximum Likelihood (ML) estimation of this process. A prime distinguishing feature of wireless sensor networks is the spatial correlation among measurements of nearby sensors. We investigate the way spatial correlation shapes the tradeoff between estimation quality and energy efficiency, according to which more measurement data improve estimation quality, but they are more energy-costly to transport. If the effect of spatial correlation is understood, then a given estimation quality can be achieved with minimum data redundancy and energy consumption. We study the dynamic control of the sensor sampling rates and the routes to the FC. Sensor attributes such as spatial correlation, measurement accuracy and energy reserve as well as the quality of wireless links, collectively affect the sampling rates and routes to the FC. Further, due to spatial correlation, sensor sampling rates alter the joint probability density functions (p.d.f’s) for sensor readings and thus they affect the average estimation error. We show that the optimization problem can be decomposed into smaller ones, where each sensor autonomously takes its sampling rate and next-hop forwarding decisions, and we propose an iterative, low-overhead primal–dual algorithm. Our work yields interesting insights on the fundamental tradeoff between network lifetime and estimation quality, it provides a clear intuition on when spatial correlation is beneficial for the tradeoff above, and it provides a solution with distributed sensor coordination.

Combining multi-path forwarding and packet aggregation for improved network performance in wireless mesh networks

Wireless mesh networks (WMNs) based on the IEEE 802.11 standard are becoming increasingly popular as a viable alternative to wired networks. WMNs can cover large or difficult to reach areas with low deployment and management costs. Several multi-path routing algorithms have been proposed for such kind of networks with the objective of load balancing the traffic across the network and providing robustness against node or link failures. Packet aggregation has also been proposed to reduce the overhead associated with the transmission of frames, which is not negligible in IEEE 802.11 networks. Unfortunately, multi-path routing and packet aggregation do not work well together, as they pursue different objectives. Indeed, while multi-path routing tends to spread packets among several next-hops, packet aggregation works more efficiently when several packets (destined to the same next-hop) are aggregated and sent together in a single MAC frame. In this paper, we propose a technique, called aggregation aware forwarding, that can be applied to existing multi-path routing algorithms to allow them to effectively exploit packet aggregation so as to significantly increase their network performance. In particular, the proposed technique does not modify the path computation phase, but it just influences the forwarding decisions by taking the state of the sending queues into account. We demonstrated our proposed technique by applying it to Layer-2.5, a multi-path routing and forwarding paradigm for WMNs that has been previously proposed. We conducted a thorough performance evaluation by means of the ns-3 network simulator, which showed that our technique allows to increase the performance both in terms of network throughput and end-to-end delay.

Time-optimized contextual information forwarding in mobile sensor networks

We study on the forwarding of quality contextual information in mobile sensor networks (MSNs). Mobile nodes form ad-hoc distributed processing networks that produce accessible and quality-stamped information about the surrounding environment. Due to the dynamic network topology of such networks the context quality indicators seen by the nodes vary over time. A node delays the context forwarding decision until context of better quality is attained. Moreover, nodes have limited resources, thus, they have to balance between energy conservation and quality of context. We propose a time-optimized, distributed decision making model for forwarding context in a MSN based on the theory of optimal stopping. We compare our findings with certain context forwarding schemes found in the literature and pinpoint the advantages of the proposed model.

A Multimetric, Map-Aware Routing Protocol for VANETs in Urban Areas

In recent years, the general interest in routing for vehicular ad hoc networks (VANETs) has increased notably. Many proposals have been presented to improve the behavior of the routing decisions in these very changeable networks. In this paper, we propose a new routing protocol for VANETs that uses four different metrics. which are the distance to destination, the vehicles' density, the vehicles' trajectory and the available bandwidth, making use of the information retrieved by the sensors of the vehicle, in order to make forwarding decisions, minimizing packet losses and packet delay. Through simulation, we compare our proposal to other protocols, such as AODV (Ad hoc On-Demand Distance Vector), GPSR (Greedy Perimeter Stateless Routing), I-GPSR (Improvement GPSR) and to our previous proposal, GBSR-B (Greedy Buffer Stateless Routing Building-aware). Besides, we present a performance evaluation of the individual importance of each metric to make forwarding decisions. Experimental results show that our proposed forwarding decision outperforms existing solutions in terms of packet delivery.

Scalable Name Lookup with Adaptive Prefix Bloom Filter for Named Data Networking

In Named Data Networking (NDN), packet forwarding decisions rely upon lookup operations on variable-length hierarchical names instead of fixed-length host addresses. This pivotal feature introduces new challenges in the deployment of NDN at the Internet scale. In this letter, a novel Name Lookup engine with Adaptive Prefix Bloom filter (NLAPB) is conceived, in which each NDN name/prefix is split into B-prefix followed by T-suffix. B-prefix is matched by Bloom filters whereas T-suffix is processed by the small-scale trie. The length of B-prefixes (and T-suffixes) is dynamically throttled based on their popularity in order to accelerate the lookup. Experimental results show that: (i) NLAPB is able to lower the false positive rate with respect to a lookup entirely based on Bloom filters; (ii) it decreases the memory requirements with respect to a trie-based approach; (iii) it reduces processing time with respect to both them.

A Unified Unicast and Multicast Routing and Forwarding Algorithm for Software-Defined Datacenter Networks

In this article, we consider a scalability problem associated with software-defined datacenter, of which the unicast/multicast routing states is proven to be NP-complete. We introduce an efficient multiple membership query algorithm, called Scalar-pair Vectors Routing and Forwarding (SVRF), based on the prime theory such as Chinese Remainder Theorem (CRT). Our proposed algorithm simply calculates corresponding output ports of each multicast group by dividing a common scalar-pair with a group-specific key, within pseudo-polynomial time. The result is then used to make a forwarding decision within few cycles through a hardware accelerator. Compared to Bloom filter, our algorithm can achieve remarkable performance in terms of memory consumption, processing time, hardware cost, and 100% delivery accuracy, while applying for a large number of large-scale distinct flows (including unicast and multicast) in a large-scale datacenter networks. Our work may be applied to various research areas of computer science and networking.

The EHU-OEF: An OpenFlow-based Layer-2 experimental facility

The current limitations of the Internet have prompted the appearance of the Future Internet initiative, which promotes the deployment of newly proposed infrastructures. In this context, experimental facilities emerge to provide realistic scenarios that allow the testing and advance the research of these novel approaches. From a technical standpoint, building a facility’s infrastructure is challenging and demanding because several requirements, such as its flexibility, support for multiple experiments, isolation and virtualisation, must be fulfilled. To investigate potential Future Internet initiatives, we designed, developed, and deployed our own experimental facility that addresses the aforementioned requirements: the EHU OpenFlow Enabled Facility (EHU-OEF). In this article, we present the EHU-OEF, which is a campus-wide facility based on OpenFlow that simultaneously supports both research and production traffic over the same infrastructure. Because this facility is based, in particular, on the OpenFlow technology and, more generally, follows the Software Defined Networking paradigm, the EHU-OEF provides researchers with the ability to programme the network. Thanks to this property, flexibility and isolation of both the control and the data planes among the experiments are addressed. This article also presents a novel method of network virtualisation at the link layer, the L2PNV approach, which ensures scalability by aggregating MAC addresses. This approach has been implemented with a modification of the FlowVisor controller originally developed at Stanford, which is a special-purpose OpenFlow controller that introduces a software slicing layer between OpenFlow switches and multiple OpenFlow controllers. This article also presents other contributions that have been developed through a successful deployment methodology in the facility, including an authentication and authorisation module, a MAC configuration module and a Prefix-Based Forwarding Decision module. In conclusion, the EHU-OEF facility possesses an excellent infrastructure designed to test and to validate novel proposals under real conditions, and this facility acts as a stepping stone for Future Internet testbeds.