Routing Cost Function Research Articles

A Realtime Adaptive Trust Model Based on Artificial Neural Networks for Wireless Sensor Networks

Wireless sensor networks (WSNs) are vulnerable to security attacks due to the unbounded nature of the wireless medium, restricted node resources, and cooperative routing. Standard cryptography and authentication mechanisms help protect against external attacks, but a compromised node can easily bypass them. This work aims to protect WSNs against internal attacks, which are mostly launched from compromised nodes to disrupt the network’s operation and/or reduce its performance. The trust and reputation management framework provides a routing cost function for selecting the best secure next hop. Tuning the trust weights is essential to cope with the constant changes in the network environment, such as the sensor nodes’ behaviours and locations. To allow real-time operation, the proposed framework introduces an artificial neural network (ANN) in each sensor node that automatically adjusts the weights of the considered trust metrics according to the WSN state. A large dataset is generated to train and test the ANN using a multitude of simulated cases. A prototype is developed and tested using the J-Sim simulator to show the performance gain resulting from applying the adaptive trust model. The experimental results showed that the adaptive model has robust performance and has achieved an improved packet delivery ratio with reduced power consumption and reduced average packet loss. The results showed that when sensor nodes were static and malicious nodes were present, the average accuracy was 99.6%, while when they were in motion, it was 88.1%.

QoS-Aware Multipath Routing in Software-Defined Networks

The emergence of new applications, such as online gaming and virtual reality, necessitates the underlying network capable of fulfilling high bandwidth and low latency requirements. The software-defined multipath routing is a viable approach to fulfill such quality-of-service (QoS) requirements by improving the data delivery performance through multipath. In this paper, we propose a QoS-aware dynamic multipath routing scheme for enhancing QoS of high-bandwidth applications in an SDN-enabled network. The proposed scheme consists of three phases – flow splitting, multipath routing, and flow reordering. In the first phase, we propose a flow splitting scheme to decide how to split the incoming flows to enable multipath routing in the network. In the second phase, we design a cost function for routing the splittable subflows and formulate a min-cost routing problem as an integer linear program (ILP). To solve the problem in polynomial time, we propose a greedy heuristic approach. Finally, in the third phase, we propose a flow reordering scheme for the received subflows through multiple paths to maintain the desired flow sequence at the destination. The experimental results show that the proposed scheme achieves higher network throughput by 22% compared to the benchmark schemes. Further, the proposed scheme achieves a reduction in QoS violated flows by 24% compared to the benchmark schemes.

CITIZEN PARTICIPATION & DIGITAL TOOLS TO IMPROVE PEDESTRIAN MOBILITY IN CITIES

Abstract. In this work, we present a framework supported by mobile and web apps and able to propose personalized pedestrian routes that match user mobility profile considering mobility impediments factors. We explain how these later have been defined using a pedestrian-centric approach based on travel experiences as perceived in the field by senior citizens. Through workshops, six main factors that may influence pedestrian route choices were revealed: passability, obstacle in path, surface problem, security, sidewalk width, slope. These categories were used to build digital tools and guide a citizen participatory approach to collect geolocated points of obstacle documented with walkability information (picture, category, impact score, free comment). We also involved citizens to evaluate these information and especially senior referents for validation. Finally we present how we connect these points of obstacle with a pedestrian network based on OpenStreetMap to configure a routing cost function. The framework has been partially deployed in 2020 with limited people due to the pandemic. Nonetheless, we share lessons learned from interaction with citizens in the design of such a framework whose underlying workflow is reproducible. We plan to further assess its relevance and sustainability in the future.

RO-RO: Routing Optimality - Reconfiguration Overhead Balance in Software-Defined ISP Networks

Software-defined networking provides a promising solution for traffic engineering (TE) by utilizing a centralized controller to remotely configure programmable network switches. In order to achieve optimal traffic distribution and meet the Quality of Service (QoS) requirements, the SDN controller must frequently solve complex optimization models. Applying an optimization model in ISP (Internet Service Provider) networks implies abundant routing reconfigurations, which adversely impact the network stability and QoS parameters. Namely, since routing updates usually cannot be applied on all switches at the same time, transient congestion and loops often happen as a result. Here, in this paper, we propose a new control framework that strives to maximize the network throughput and provide QoS with minimal reconfiguration costs. In contrast to the conventional TE approaches, which perform the network optimizations periodically and control the side effects of reconfigurations by carefully choosing the period length between the optimization cycles, we propose a multi-objective optimization model which jointly minimizes the routing cost function and the reconfiguration overhead. The Pareto frontier of the optimization model is generated by the augmented ∈-constrained method, whereas a Lyapunov drift-plus-penalty function is used to select the best compromise solution from the Pareto set. Since the reconfiguration overhead is reduced, the network controller could be allowed to optimize resource allocation more frequently, in order to respond quickly and efficiently to the network changes. Considering that the proposed optimization model is computationally intractable in large-scale networks, we also propose a heuristic algorithm to efficiently solve large instances of the problem. In simulations and Mininet experiments, we show that our solution brings performance improvement over the conventional periodic TE techniques. Moreover, the proposed heuristic achieves better QoS request acceptance ratio than the state-of-the-art multi-objective optimization solution, despite the significantly reduced computational complexity.

Performance evaluation of various link quality metrics using cross layer routing for wireless multimedia sensor networks

For the past few years, link quality estimation has been an active area of research in wireless networks. Low-power wireless links are error-prone, asymmetric and unreliable in nature. Therefore, understanding the behaviour and characteristics of low-power radio links is essential to design effective and efficient routing protocol in wireless networks. The objective of this paper is to estimate and evaluate the quality of a link with single link quality metric and amalgamated link quality metric. In addition, these estimated link quality metrics are respectively used in a generic routing cost function of the proposed link quality-based cross layer routing (LQCLR) protocol. Extensive simulation results are presented, which give insights on how estimated link quality with single and amalgamated link quality metrics affects the performance of routing protocol in wireless multimedia sensor network (WMSN).

Performance evaluation of various link quality metrics using cross layer routing for wireless multimedia sensor networks

For the past few years, link quality estimation has been an active area of research in wireless networks. Low-power wireless links are error-prone, asymmetric and unreliable in nature. Therefore, understanding the behaviour and characteristics of low-power radio links is essential to design effective and efficient routing protocol in wireless networks. The objective of this paper is to estimate and evaluate the quality of a link with single link quality metric and amalgamated link quality metric. In addition, these estimated link quality metrics are respectively used in a generic routing cost function of the proposed link quality-based cross layer routing (LQCLR) protocol. Extensive simulation results are presented, which give insights on how estimated link quality with single and amalgamated link quality metrics affects the performance of routing protocol in wireless multimedia sensor network (WMSN).

A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data.

In this work, we present a system that generates customized pedestrian routes entirely based on data from OpenStreetMap (OSM). The system enables users to define to what extent they would like the route to have green areas (e.g., parks, squares, trees), social places (e.g., cafes, restaurants, shops) and quieter streets (i.e., with less road traffic). We present how the greenness, sociability, and quietness factors are defined and extracted from OSM as well as how they are integrated into a routing cost function. We intrinsically evaluate customized routes from one-thousand trips, i.e., origin–destination pairs, and observe that these are, in general, as we intended—slightly longer but significantly more social, greener, and quieter than the respective shortest routes. Based on a survey taken by 156 individuals, we also evaluate the system’s usefulness, usability, controlability, and transparency. The majority of the survey participants agree that the system is useful and easy to use and that it gives them the feeling of being in control regarding the extraction of routes in accordance with their greenness, sociability, and quietness preferences. The survey also provides valuable insights into users requirements and wishes regarding a tool for interactively generating customized pedestrian routes.

Multi-Metric Route Cost Based Routing in Wireless Multimedia AD-HOC Networks

To improve the quality of life, bigger cities in the world addressing their problems by adopting latest technology. IOT connect physical world to the internet and such concept is adopted by bigger cities having large population growth rate. Wireless multimedia sensor network helps to monitor various parts of a city without use of cables. This network becomes the primary component of every smart city due to its surveillance and monitoring capability In contrast with conventional sensor networks, multimedia sensor nodes are equipped with cameras which acquire, process, compress and transmit information about an event happing at some remote area in the form of an image or video. However, like conventional WSNs this network is having multiple constrained and new metric needs to be considered to improve network life time and Quality of service parameters. Multiple metric based route cost function is defined and routing mechanism based upon this cost function is proposed. Since each multimedia sensor node is battery operated and connected through low power wireless links. This work helps to find an optimal path having minimum energy consumption, maximum link reliability, minimum number of hops and minimum routing table magnitude. A cost function considers constraints of wireless multimedia sensor networks. It satisfies desirable network requirements and improves network life time through efficient routing. The proposed algorithm is tested, simulated and compared with previous routing algorithms.

Bi-Objective Cost Function for Adaptive Routing in Network-on-Chip

This paper proposes a new fully adaptive routing protocol for 2D-mesh Network-on-Chip (NoCs). It is inspired from the A-star search algorithm and called Heuristic based Routing Algorithm (HRA). It is distributed, congestion-aware, and fault-tolerant by using only the local information of each router neighbors. HRA does not use Virtual Channels (VCs) but tries to reduce the risk of deadlock by avoiding the 2-nodes and the 4-nodes loops. HRA is based on a bi-objective weighted sum cost function. Its goal is optimizing latency and throughput. Experiments show that HRA ensures a good reliability rate despite the presence of many faulty links. In addition, our approach reports interesting latencies and average throughput values when a non-dominated solution is chosen.

Multi-objective Node Placement Considering Non-uniform Event Pattern

Ease of use, high flexibility and variety of applications have made wireless sensor networks very popular. Node placement in a sensor network is very critical since it affects important network attributes such as coverage, lifetime, and reliability. Therefore, controlled node placement is necessary for achieving specific network features with minimum number of nodes. Since node placement is an NP-hard problem, many placement algorithms have been proposed based on heuristic and meta-heuristic methods. Most of those algorithms assume a uniform event pattern (UEP) throughout the area under investigation. However, in practice some networks deal with non-uniform event pattern (NEP). Optimization of one attribute of the network usually results in degradation of other attributes. That is why in recent studies multi-objective optimization methods have been used which usually provide a set of best answers while the final answer is selected by a decision maker applying a trade-off between all attributes. In this paper a method for controlled node placement is proposed based on multi-objective optimization (MOO) algorithms considering a non-uniform event pattern for the network (NPNEP). In that sense this method is an extension of the previous methods that use uniform event pattern. Because of the good performance of multi-objective optimization evolutionary algorithm based on decomposition (MOEA/D), it is utilized as the optimization tool in node placement. In order to use MOEA/D, a few objective functions are defined which can optimize important attributes like coverage, power consumption, delay, reliability and lifetime. In order to achieve optimal node utilization, load balance, and increased lifetime, a cost function for routing is proposed as well as a data gathering and reporting method which both help increase the lifetime of a network. The proposed method can be used for wireless sensor networks with heterogeneous nodes. This algorithm can be used in initial deployment phase as well as operation phase or when problems like fragmentation or loss of coverage occurs. The result of NPNEP algorithm is the initial position of nodes or position of the new nodes which provide the best answers in MOO algorithm. Performance of the proposed algorithm and the effect of NEP as opposed to UEP have been verified by simulations.

A discrete dynamical system of formulating traffic assignment: Revisiting Smith’s model

Through relaxing the behavior assumption adopted in Smith’s model (Smith, 1984), we propose a discrete dynamical system to formulate the day-to-day evolution process of traffic flows from a non-equilibrium state to an equilibrium state. Depending on certain preconditions, the equilibrium state can be equivalent to a Wardrop user equilibrium (UE), Logit-based stochastic user equilibrium (SUE), or boundedly rational user equilibrium (BRUE). These equivalence properties indicate that, to make day-to-day flows evolve to equilibrium flows, it is not necessary for travelers to choose their routes based on actual travel costs of the previous day. Day-to-day flows can still evolve to equilibrium flows provided that travelers choose their routes based on estimated travel costs which satisfy these preconditions. We also show that, under a more general assumption than the monotonicity of route cost function, the trajectory of the dynamical system converges to a set of equilibrium flows by reasonably setting these parameters in the dynamical system. Finally, numerical examples are presented to demonstrate the application and properties of the dynamical system. The study is helpful for understanding various processes of forming traffic jam and designing an algorithm for calculating equilibrium flows.

Survey of QoS Routing Protocols in Wireless Multimedia Sensor Networks

The emergence of Wireless Multimedia Sensor Networks (WMSNs) has stimulated the refocusing of research from conventional scalar Wireless Sensor Networks (WSNs) to WMSNs. Currently, because of their prevalence WMSNs are used in different applications. Due to the unique features of WMSNs, fulfilling Quality of Service (QoS) requirements for a variety of applications is the challenge. QoS routing is a backbone of WMSNs and plays a vital role in satisfying QoS requirements. The performance of QoS routing depends upon the selection of an optimal path or paths. Path selection is based on evaluation of a cost function using various routing metrics. A careful blend of such metrics in a routing cost function guarantees a committed level of QoS. This survey uses number of routing metrics as criteria for categorizing state-of-the-art QoS WMSNs routing techniques. In addition, open issues and future research directions to further develop efficient routing protocols to guarantee QoS are discussed.

A Modified Levenberg-Marquardt (L-M) Algorithm for Traffic Equilibrium Problem with Nonadditive Route Costs

The traditional traffic equilibrium problem (TEP) is mainly based on the additivity assumption that the route cost is simply the sum of the link costs on that route. However, there are many situations where this assumption on the route costs is inappropriate, and thus we have to explicitly formulate and solve the TEP in the route space instead of link space. In this paper, we firstly reformulate the TEP with nonadditive route cost function to a nonlinear complementarity problem (NCP), and then the NCP is converted to an equivalent least square problem (LSP) with a new NCP function; then we propose a modified Levenberg- Marquardt algorithm to solve the LSP, and also, the quadratic convergence and the equivalent condition of the proposed L-M algorithm are proved under some assumptions. Finally, a numerical example is presented in the paper. As the results shown, the proposed method has the capability to converge to a high level accuracy with reasonable computational efforts.

ENERGY EFFICIENT GEOGRAPHIC ROUTING ALGORITHMS IN WIRELESS SENSOR NETWORK

Over the past decade, energy efficiency has consistently been a critical research topic in the field of wireless sensor networks. In wireless networks, signal interference often leads to power waste in a sensor node. Several SINR-based routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or may slow in routing computation speed. In this paper, two energy efficient geographic routing algorithms (EEGRA) for wireless sensor network are proposed to address the power consumption issue while considering the routing computation speed. The first algorithm take the value of interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We adopt four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, in EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The experimental result shows that the EEGRA algorithms reduce energy consumption by 30–50% comparing to geographic routing methods. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.

A complementary formulation for traffic equilibrium problem with a new nonadditive route cost

Improving transportation system is essential for all people in each city since transport plays a very important role. Using mathematical programming approach transport problem is an effective way to improve transportation system. In this paper, the traffic equilibrium problem (TEP) with a general nonadditive route cost function is studied. We formulate the route cost function for each route as a disutility function, which can evaluate route cost function flexibly and analyze the route toll conveniently. Furthermore, we present the TEP with a nonlinear complementary problem (NCP) formulation. The monotonicity and the existence with the NCP formulation are also given under relative assumptions.

A semismooth Newton method for traffic equilibrium problem with a general nonadditive route cost

Computing traffic equilibria with a general nonadditive route cost disutility function is considered in this paper. Following the user equilibrium (UE) condition, that is, no driver can unilaterally change route to achieve less travel costs, the traffic equilibrium problem (TEP) can be formulated as a nonlinear complementary problem (NCP). In this paper, we propose a semismooth Newton method with a penalized Fischer–Burmeister (PFB) NCP function to solve the NCP formulation of the TEP, and also, we investigate the properties of the proposed method. Numerical results are provided and compared with the classical TEP with additive route cost functions. The results show the algorithm can achieved substantially better performance than the existing approaches. A sensitivity analysis is also conducted to examine the parameter of the proposed nonadditive route cost function.

Convergence to Equilibrium in Dynamic Traffic Networks when Route Cost Is Decay Monotone

This paper addresses the issue of convergence to equilibrium in dynamic traffic assignment. Within-day time is considered to be a continuous variable, so that traffic flows and costs are functions of within-day time. Flow propagates along routes connecting origin-destination (OD) pairs with the demand for travel between each OD pair considered to be rigid (fixed from day to day although it can vary within day). Day-to-day time is also modelled as continuous with the day-to-day dynamical system derived naturally from the usual dynamical user equilibrium (DUE) condition. This paper focuses on the bottleneck model, which has deterministic vertical queueing at bottleneck link exits when flow exceeds capacity. A new property called decay monotonicity is introduced. The link delay (and hence link cost) function is shown to be a decay monotone function of link flow provided that the link capacity is continuously differentiable and positive. In a restricted version of the single bottleneck per route case, it is shown that link cost decay monotonicity implies route cost decay monotonicity. Decay monotonicity of the route cost function is shown to be sufficient for convergence to equilibrium of the dynamical system.

On selecting the cost function for source routing

Many proposed source routing algorithms tackle the Multiple Additively Constrained Path (MACP) selection, an NP-complete problem, by transforming it into the shortest path selection problem, which is P-complete, with an integrated cost function that maps the multi-constraints of each link into a single cost. However, how to select an appropriate cost function is an important issue that has rarely been addressed in literature. In this paper, we provide a theoretical framework for picking a cost function that can improve the performance of source routing in terms of complexity, convergence, and probability of finding a feasible path.

Convergence in a continuous dynamic queueing model for traffic networks

The paper considers a dynamic traffic assignment model with deterministic queueing and inelastic demand for each origin–destination (OD) pair in the network. Two types of time-varying behaviour are modelled. First, within-day time is regarded as a continuous variable. During each day, flows propagating through routes connecting OD pairs are represented by non-negative, essentially bounded and measurable functions. Also, day-to-day time is (slightly surprisingly) modelled as if it were continuous. The day-to-day dynamical system that is adopted is derived naturally from the usual user equilibrium condition. The route cost is shown to be a Lipschitz continuous function of route flow in the single bottleneck per route case. Global convergence to equilibrium is shown to be guaranteed when the route cost vector is a non-decreasing (monotone) function of the route flow vector. In the single bottleneck per route case, the route cost function is shown to be a monotone function of the route flow if the bottleneck capacities are all non-decreasing as functions of within-day time. Monotonicity of the route cost function is also shown to hold when each bottleneck has at most one route passing through it.

Traffic equilibrium problem with route-specific costs: formulation and algorithms

Using a new gap function recently proposed by Facchinei and Soares [Facchinei, F., Soares, J., 1995. Testing a new class of algorithms for nonlinear complementarity problems. In: Giannessi, F., Maugeri, A. (Eds.), Variational Inequalities and Network Equilibrium Problems. Plenum Press, New York], we convert the nonlinear complementarity problem (NCP) formulation for the traffic equilibrium problem to an equivalent unconstrained optimization. This equivalent formulation uses both route flows and the minimum origin–destination travel costs as the decision variables. Two unique features of this formulation are that: (i) it can model the traffic assignment problem with a general route cost structure; (ii) it is smooth, unconstrained, and that every stationary point of the minimization corresponds to a global minimum. These properties permit a number of efficient algorithms for its solution. Two solution approaches are developed to solve the proposed formulation. Numerical results using a route-specific cost structure are provided and compared with the classic traffic equilibrium problem, which assumes an additive route cost function.