An autonomic routing framework for sensor networks

Current routing services for sensor networks are often designed for specific applications and network conditions, thus have difficulty in adapting to application and network dynamics. This paper proposes an autonomic framework to promote the adaptivity of routing services in sensor networks. The key idea of this framework is to maintain some feature functions that are decoupled from originally-integrated routing services. This separation enables significant service changes to be done by only tuning these functions. Measures including parameterization are taken to save the energy for changing these functions. Further, this framework includes a monitoring module to support a policy-based collaborative adaptation. This paper shows an example autonomic routing service conforming to this framework. Some of this work was done while the author was at ISI     

DyRAM: An Active Reliable Multicast Framework for Data Distribution

Group communications (multicast) are foreseen to be one of the most critical yet challenging technologies to meet the exponentially growing demands for data distribution in a large variety of applications of the Internet (such as grid computing, web applications and distributed simulations). When reliability is required, there is no straightforward solutions and meeting the objectives of reliable multicast is not an easy task. Active networks open a new perspective in providing more efficient solutions for the problem of reliability. In this context, routers are able to perform customized computations on the packets flowing through them. In this paper, we propose a receiver-based (replier) local recovery multicast protocol with dynamic repliers elected on a per-packet basis. Designed to provide an efficient reliable multicast service without any cache facilities inside the network, our approach, uses low-overhead active services in routers. The current paper addresses the design, evaluation and the implementation of an efficient and scalable reliable multicast protocol noted DyRAM standing for Dynamic Replier Active reliable multicast.     

Using Trust to Secure Geographic and Energy Aware Routing against Multiple Attacks

To address the vulnerability of geographic routing to multiple security threats such as false routing information, selective forwarding and the Sybil attack in wireless sensor networks, this paper proposes a trust-based defending model against above-mentioned multiple attacks. Considering the characteristics of resource-constrained sensor nodes, trust values of neighboring nodes on the routing path can be calculated through the Dirichlet distribution function, which is based on data packets'' acknowledgements in a certain period instead of energy-consuming monitoring. Trust is combined with the cost of geographic and energy aware routing for selecting the next hop of routing. At the same time, the initial trust is dynamically determined, service requests are restricted for malicious nodes in accordance with trust values, and the impact of node mobility is weakened by the trust evolution. The simulation results and analysis show that the proposed model under multiple attacks has advantages in packet delivery ratio and network lifetime over the existing models.     

Health Concerns Versus Mobile Data Needs: Conjoint Measurement of Preferences for Mobile Communication Network Scenarios

As demands for mobile broadband services and ubiquitous network coverage in our societies are increasing, the mobile communication network infrastructure has to be expanded. Concurrently, the technical infrastructure of mobile communication technologies (base stations) raises the public's concerns about health risks due to electromagnetic fields (EMF). By applying conjoint analyses, the study empirically investigates the relationship between mobile data demands, different base station locations, the prevalence of perceived health complaints, and the impact of compensation payments. Findings show that health concerns are the most critical factor for mobile network communication scenario preferences, followed by data rate availability. In the decision scenarios, base station location and compensation payments played a minor role. Two user groups, cellphone and smart phone users who differ in their sensitivity regarding health concerns and data demands, were identified by segmentation analysis. By means of a sensitivity analysis, different mobile communication network scenarios were analyzed. Outcomes show the importance of integrating users’ preferences into the design of mobile communication networks. This especially refers to an increased sensitivity regarding health concerns in cellphone users and minimum requirements for data rates at least sufficient for the usage of mobile Internet services for smart phone users.     

A Dynamic Partitioning Protection Routing Technique in WDM Networks

With the increasing popularity of bandwidth-intensive applications, network traffic has been growing exponentially. Wavelength Division Multiplexing (WDM) is a technique that can harness the huge bandwidth available in an optical fiber to satisfy the network demand. Due to the multiplicity of the connections on any single link, fault tolerance is of utmost importance in such WDM networks. Active research on providing fault tolerance in WDM networks in recent times underscores its significance. In this study, a dynamic partitioning protection routing technique for routing a Fault Tolerant Path Set (FTPS) in a network is proposed. Wavelength assignment schemes to this FTPS with backup multiplexing technique for networks with no wavelength conversion and full wavelength conversion are discussed. Performance is measured in terms of blocking probability and time to recover the failed connections. Our simulations show that this protection technique performs better than other proposed techniques.     

Bi-level optimization programming for the shipper-carrier network problem

The paper presents a bi-level modeling approach that captures hierarchical relationships between shippers and carriers in maritime freight transportation networks. Ocean carriers, land carriers and port terminal operators provide transportation services at different parts of the multimodal network. Port terminal operators are regarded as a special type of carrier due to their behavior. The carriers determine service charges and delivery routes (port services) through competition and interactions among themselves. Shippers are users of the transportation services. Shippers choose a sequence of carriers, based on the carriers’ pricing and routing decisions. These relationships are captured in a bi-level model where carriers are the leaders and shippers are the followers. The paper focuses on the behavior of shippers having the transportation service information with spatial price equilibrium. A numerical example is used to demonstrate the validity of the developed model.     

Composition and structure of a large online social network in The Netherlands

Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.     

Network slicing to improve multicasting in HPC clusters

In high performance computing (HPC) resources’ extensive experiments are frequently executed. HPC resources (e.g. computing machines and switches) should be able to handle running several experiments in parallel. Typically HPC utilizes parallelization in programs, processing and data. The underlying network is seen as the only non-parallelized HPC component (i.e. no dynamic virtual slicing based on HPC jobs). In this scope we present an approach in this paper to utilize software defined networking (SDN) to parallelize HPC clusters among the different running experiments. We propose to accomplish this through two major components: A passive module (network mapper/remapper) to select for each experiment as soon as it starts the least busy resources in the network, and an SDN-HPC active load balancer to perform more complex and intelligent operations. Active load balancer can logically divide the network based on experiments’ host files. The goal is to reduce traffic to unnecessary hosts or ports. An HPC experiment should multicast, rather than broadcast to only cluster nodes that are used by the experiment. We use virtual tenant network modules in Opendaylight controller to create VLANs based on HPC experiments. In each HPC host, virtual interfaces are created to isolate traffic from the different experiments. The traffic between the different physical hosts that belong to the same experiment can be distinguished based on the VLAN ID assigned to each experiment. We evaluate the new approach using several HPC public benchmarks. Results show a significant enhancement in experiments’ performance especially when HPC cluster experiences running several heavy load experiments simultaneously. Results show also that this multi-casting approach can significantly reduce casting overhead that is caused by using a single cast for all resources in the HPC cluster. In comparison with InfiniBand networks that offer interconnect services with low latency and high bandwidth, HPC services based on SDN can provide two distinguished objectives that may not be possible with InfiniBand: The first objective is the integration of HPC with Ethernet enterprise networks and hence expanding HPC usage to much wider domains. The second objective is the ability to enable users and their applications to customize HPC services with different QoS requirements that fit the different needs of those applications and optimize the usage of HPC clusters.     

Modeling,analysis and simulation of ant-based network routing protocols

Using the metaphor of swarm intelligence, ant-based routing protocols deploy control packets that behave like ants to discover and optimize routes between pairs of nodes. These ant-based routing protocols provide an elegant, scalable solution to the routing problem for both wired and mobile ad hoc networks. The routing problem is highly nonlinear because the control packets alter the local routing tables as they are routed through the network. We mathematically map the local rules by which the routing tables are altered to the dynamics of the entire networks. Using dynamical systems theory, we map local protocol rules to full network performance, which helps us understand the impact of protocol parameters on network performance. In this paper, we systematically derive and analyze global models for simple ant-based routing protocols using both pheromone deposition and evaporation. In particular, we develop a stochastic model by modeling the probability density of ants over the network. The model is validated by comparing equilibrium pheromone levels produced by the global analysis to results obtained from simulation studies. We use both a Matlab simulation with ideal communications and a QualNet simulation with realistic communication models. Using these analytic and computational methods, we map out a complete phase diagram of network behavior over a small multipath network. We show the existence of both stable and unstable (inaccessible) routing solutions having varying properties of efficiency and redundancy depending upon the routing parameters. Finally, we apply these techniques to a larger 50-node network and show that the design principles acquired from studying the small model network extend to larger networks.     

Using Trust to Establish a Secure Routing Model in Cognitive Radio Network

Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes’ forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes’ trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.     

Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks

Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains.     

Twitter: A Good Place to Detect Health Conditions

With the proliferation of social networks and blogs, the Internet is increasingly being used to disseminate personal health information rather than just as a source of information. In this paper we exploit the wealth of user-generated data, available through the micro-blogging service Twitter, to estimate and track the incidence of health conditions in society. The method is based on two stages: we start by extracting possibly relevant tweets using a set of specially crafted regular expressions, and then classify these initial messages using machine learning methods. Furthermore, we selected relevant features to improve the results and the execution times. To test the method, we considered four health states or conditions, namely flu, depression, pregnancy and eating disorders, and two locations, Portugal and Spain. We present the results obtained and demonstrate that the detection results and the performance of the method are improved after feature selection. The results are promising, with areas under the receiver operating characteristic curve between 0.7 and 0.9, and f-measure values around 0.8 and 0.9. This fact indicates that such approach provides a feasible solution for measuring and tracking the evolution of health states within the society.     

Dynamic Source Routing Strategy for Two-Level Flows on Scale-Free Networks

Packets transmitting in real communication networks such as the Internet can be classified as time-sensitive or time-insensitive. To better support the real-time and time-insensitive applications, we propose a two-level flow traffic model in which packets are labeled as level-1 or level-2, and those with level-1 have higher priority to be transmitted. In order to enhance the traffic capacity of the two-level flow traffic model, we expand the global dynamic routing strategy and propose a new dynamic source routing which supports no routing-flaps, high traffic capacity, and diverse traffic flows. As shown in this paper, the proposed dynamic source routing can significantly enhance the traffic capacity and quality of time-sensitive applications compared with the global shortest path routing strategy.     

VNF-EQ: dynamic placement of virtual network functions for energy efficiency and QoS guarantee in NFV

With the advances of network function virtualization and cloud computing technologies, a number of network services are implemented across data centers by creating a service chain using different virtual network functions (VNFs) running on virtual machines. Due to the complexity of network infrastructure, creating a service chain requires high operational cost especially in carrier-grade network service providers and supporting stringent QoS requirements from users is also a complicated task. There have been various research efforts to address these problems that only focus on one aspect of optimization goal either from users such as latency minimization and QoS based optimization, or from service providers such as resource optimization and cost minimization. However, meeting the requirements both from users and service providers efficiently is still a challenging issue. This paper proposes a VNF placement algorithm called VNF-EQ that allows users to meet their service latency requirements, while minimizing the energy consumption at the same time. The proposed algorithm is dynamic in a sense that the locations or the service chains of VNFs are reconfigured to minimize the energy consumption when the traffic passing through the chain falls below a pre-defined threshold. We use genetic algorithm to formulate this problem because it is a variation of the multi-constrained path selection problem known as NP-complete. The benchmarking results show that the proposed approach outperforms other heuristic algorithms by as much as 49% and reduces the energy consumptions by rearranging VNFs.     

Development of Veterinary Laboratory Networks for Avian Influenza and Other Emerging Infectious Disease Control: The Southeast Asian Experience

The outbreak of highly pathogenic H5N1 avian influenza, with its international spread, confirmed that emerging infectious disease control must be underpinned by effective laboratory services. Laboratory results are the essential data underpinning effective surveillance, case diagnosis, or monitoring of responses. Importantly, laboratories are best managed within national and international networks of technological support rather than in isolation. A well planned laboratory network can deliver both a geographical spread of testing capacity and also a cost effective hierarchy of capability. Hence in the international context regional networks can be particularly effective. Laboratories are an integral part of a country’s veterinary services and their role and function should be clearly defined in the national animal health strategy and supporting government policies. Not every laboratory should be expected to deliver every possible service, and integration into regional and broader international networks should be a part of the overall strategy. The outputs required of each laboratory should be defined and then ensured through accredited quality assurance. The political and scientific environment in which laboratories operate changes continuously, not only through evolving national and regional animal health priorities but also through new test technologies and enhancements to existing technologies. Active networks help individual laboratories to monitor, evaluate, and respond to such challenges and opportunities. The end result is enhanced emerging infectious disease preparedness across the region.     

Slime mold inspired routing protocols for wireless sensor networks

Many biological systems are composed of unreliable components which self-organize effectively into systems that achieve a balance between efficiency and robustness. One such example is the true slime mold Physarum polycephalum which is an amoeba-like organism that seeks and connects food sources and efficiently distributes nutrients throughout its cell body. The distribution of nutrients is accomplished by a self-assembled resource distribution network of small tubes with varying diameter which can evolve with changing environmental conditions without any global control. In this paper, we exploit two different mechanisms of the slime mold??s tubular network formation process via laboratory experiments and mathematical behavior modeling to design two corresponding localized routing protocols for wireless sensor networks (WSNs) that take both efficiency and robustness into account. In the first mechanism of path growth, slime mold explores its immediate surroundings to discover and connect new food sources during its growth cycle. We adapt this mechanism for a path growth routing protocol by treating data sources and sinks as singular potentials to establish routes from the sinks to all the data sources. The second mechanism of path evolution is the temporal evolution of existing tubes through nonlinear feedback in order to distribute nutrients efficiently throughout the organism. Specifically, the diameters of tubes carrying large fluxes of nutrients grow to expand their capacities, and tubes that are not used decline and disappear entirely. We adapt the tube dynamics of the slime mold for a path evolution routing protocol. In our protocol, we identify one key adaptation parameter to adjust the tradeoff between efficiency and robustness of network routes. Through extensive realistic network simulations and ideal closed form or numerical computations, we validate the effectiveness of both protocols, as well as the efficiency and robustness of the resulting network connectivity.     

Resource Management for Ad-Hoc Wireless Networks with Cluster Organization

Boosted by technology advancements, government and commercial interest, ad-hoc wireless networks are emerging as a serious platform for distributed mission-critical applications. Guaranteeing QoS in this environment is a hard problem because several applications may share the same resources in the network, and mobile ad-hoc wireless networks (MANETs) typically exhibit high variability in network topology and communication quality. In this paper we introduce DYNAMIQUE, a resource management infrastructure for MANETs. We present a resource model for multi-application admission control that optimizes the application admission utility, defined as a combination of the QoS satisfaction ratio. A method based on external adaptation (shrinking QoS for existing applications and later QoS expansion) is introduced as a way to reduce computation complexity by reducing the search space. We designed an application admission protocol that uses a greedy heuristic to improve application utility. For this, the admission control considers network topology information from the routing layer. Specifically, the admission protocol takes benefit from a cluster network organization, as defined by ad-hoc routing protocols such as CBRP and LANMAR. Information on cluster membership and cluster head elections allows the admission protocol to minimize control signaling and to improve application quality by localizing task mapping.     

Introducing accessibility analysis in mapping cultural ecosystem services

In recent years, there has been an increasing interest in the study of the spatial link between service providing areas (SPA) and service benefiting areas (SBA). Understanding the spatial link between SPAs and SBAs is essential when studying the ecosystem service delivery and the fulfilment of ecosystem service demand. However, far too little attention has been paid to the user movement related ecosystem services and where people should be geographically situated in order to benefit from these services. In the movement related services, benefiting areas are equal to providing areas and the spatial link from residential area to SPA is important. The spatial link is addressed through the concept of accessibility which determines the opportunity to move from the area where beneficiaries are located to areas where ecosystem services are produced.This study presents an accessibility approach to the ecosystem services research. Accessibility analyses offer an opportunity to identify the gap between the ecosystems’ potential to produce services and the actual usage possibilities of such services. We demonstrate the suitability of the method by using outdoor recreation and cultural heritage as examples of cultural ecosystem services that people actively want to reach. Accessibility was calculated using a geographical information system-based least-cost path analysis, which measures travel time by car between residential location and the nearest SPA via road network.The examples highlight that accessibility varies according to the ecosystem service and depends mostly on population distribution and travel possibilities. Our results demonstrate that the density of the analysed ecosystem service opportunities is higher near urban areas than elsewhere. The accessibility of different ecosystem services also depends on how much time people are willing to spend for reaching these services. Our study emphasised that, from a population perspective, accessibility analyses provide a powerful tool for illustrating the utilisation possibilities of spatially distributed ecosystem services. The accessibility approach offers great potential to assess the potential use of SPAs and respond to the need to develop a practical tool for ecosystem service research. It effectively shows, for example, the areas where the risk of overuse of ecosystem services is increased. Knowing about the regional differences in ecosystem service usage also gives background information for the decision-makers for drawing conclusions about how much and where it is sensible to invest in the maintenance of ecosystem services.     

Algorithms for energy efficient mobile object tracking in wireless sensor networks

Wireless sensor networks have found more and more applications in a variety of pervasive computing environments, in their functions as data acquisition in pervasive applications. However, how to get better performance to support data acquisition of pervasive applications over WSNs remains to be a nontrivial and challenging task. The network lifetime and application requirement are two fundamental, yet conflicting, design objectives in wireless sensor networks for tracking mobile objects. The application requirement is often correlated to the delay time within which the application can send its sensing data back to the users in tracking networks. In this paper we study the network lifetime maximization problem and the delay time minimization problem together. To make both problems tractable, we have the assumption that each sensor node keeps working since it turns on. And we formulate the network lifetime maximization problem as maximizing the number of sensor nodes who don’t turn on, and the delay time minimization problem as minimizing the routing path length, after achieving the required tracking tasks. Since we prove the problems are NP-complete and APX-complete, we propose three heuristic algorithms to solve them. And we present several experiments to show the advantages and disadvantages referring to the network lifetime and the delay time among these three algorithms on three models, random graphs, grids and hypercubes. Furthermore, we implement the distributed version of these algorithms.