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Telecommunication networks are currently realizing more-huge-than-ever data demands from subscribers all over the world. Due to the ongoing pandemic, nearly all businesses have adapted working models with remote operations. People engaged with major industries, e.g., academia, health and municipalities are utilizing online platforms to carryout their routine tasks. This indeed shifts the attention from one-to-one (unicast) communication to one-to-many (multicast) and many-to-many (multi-source multi-destination) communications. Network operators are facing increased pressure to provide quick responses in order to satisfy the bandwidth hungry and time sensitive user demands. This can only be done by enhancing deployability as well as manageability of the services. Network Function Virtualization (NFV) provides a transformation of traditional proprietary network designs to a more agile and software based environment in order to achieve flexible deployments, reduced setup costs and less-time-to-market for the new services which is very much needed in the current scenarios. Previous studies on NFV-enabled multicast problem either proposed Integer Linear Program (ILP) models, that are pretty unscalable, or heuristic-based techniques that do not guarantee good quality of the solutions obtained. In this article, we propose an NFV multicast resource optimization model exploiting the use of multiple sources and considering the end-to-end delay and bandwidth requirements. Herein, we propose a novel Dantzig-Wolfe (DW) decomposition model that tackles the complexity of the problem by breaking it down into a master problem and several pricing problems. We compare the DW approach with the ILP and heuristic methods and demonstrate that our approach achieves near to optimal solution (in comparison to heuristic based methods) much faster than ILP. We also study the dynamic admission of NFV-enabled multicast requests by solving the problem in an online manner using the batch processing of requests. We then evaluate the performance of the proposed algorithms through extensive simulations and demonstrate that proposed algorithms are promising and outperform existing solutions. [ABSTRACT FROM AUTHOR]

Network Function Virtualization (NFV) converts network functions executed by costly middleboxes into instances of Virtual Network Functions (VNFs) hosted by industry-standard Physical Machines (PMs). This has proven to be quite an efficient approach when it comes to enabling automated network operations and the elastic provisioning of resources to support heterogeneous services. Today’s revolutionary services impose a remarkably elevated reliability together with ultra-low latency requirements. Therefore, in addition to having highly reliable VNFs, these VNFs have to be optimally placed in such a way to rapidly route traffic among them with the least utilization of bandwidth. Hence, the proper selection of PMs to meet the above-mentioned reliability and delay requirements becomes a remarkably challenging problem. None of the existing publications addressing such a problem concurrently adopts VNF decomposition to enhance the flexibility of the VNFs’ placement and a hybrid routing scheme to achieve an optimal trade-off between the above-mentioned objectives. In this paper, a VNF-decomposition-based backup strategy is proposed together with a delay-aware hybrid multipath routing scheme for enhancing the reliability of NFV-enabled network services while jointly reducing delays these services experience. The problem is formulated as a Mixed Integer Linear Program (MILP) whose resolution yields an optimal VNF placement and traffic routing policy. Next, the delay-aware hybrid shortest path-based heuristic algorithm is proposed to work around the MILP’s complexity. Thorough numerical analysis and simulations are conducted to validate the proposed algorithm and evaluate its performance. Results show that the proposed algorithm outperforms its existing counterparts by 7.53% in terms of computing resource consumption. [ABSTRACT FROM AUTHOR]

Smart grid is a typical cyber-physical system, which presents the dependence of power system operations on cyber infrastructure for control, monitoring, and protection purposes. The rapid deployment of synchrophasor measurements units (PMUs) supporting wide area measurement system (WAMS) in the smart grid transmission system has opened opportunities to enhance the grid operations through the introduction of WAMS applications. However, the increased deployment of synchrophasor technologies increases the effective attack surface available to attackers and exposes WAMS applications. Such applications have strict and stringent delay requirements, e.g., end-to-end delay as well as delay variation between measurements from different PMUs. In this paper, we present a mathematical model for constructing forwarding trees for PMUs’ measurements which satisfy the end-to-end delay as well as the delay variation requirements of WAMS applications at data concentrators. We illustrate that simple shortest path routing will result in larger fraction of data drop and that our method will achieve better delivery rate. We also validate our method against delay attacks using real-time co-simulation. [ABSTRACT FROM AUTHOR]

Network Function Virtualization (NFV) has revolutionized service provisioning in cloud datacenter networks. It enables the complete decoupling of Network Functions (NFs) from the physical hardware middle boxes that network operators deploy for implementing service-specific and strictly ordered NF chains. Precisely, NFV allows for dispatching NFs as instances of plain software called virtual network functions (VNFs) running on virtual machines hosted by one or more industry standard physical machines. Nevertheless, NF softwarization introduces processing vulnerability (e.g., failures caused by hardware or software, and so on). Since any failure of VNFs could break down an entire service chain, thus interrupting the service, the functionality of an NFV-enabled network will require a higher reliability compared with traditional networks. This paper encloses an in-depth investigation of a reliability-aware joint VNF chain placement and flow routing optimization. In order to guarantee the required reliability, an incremental approach is proposed to determine the number of required VNF backups. Through illustration, it is shown herein that the formulated single path routing model can be easily extended to support resource sharing between adjacent backup VNF instances. This paper advocates the absolute existence of a share-resource-based VNF assignment strategy that is capable of trading off all of the reliability, bandwidth, and computing resources consumption of a given service chain. A heuristic is proposed to work around the complexity of the presently formulated integer linear programming (ILP). Thorough numerical analysis and simulations are conducted in order to verify and assert the validity, correctness, and effectiveness of this proposed heuristic reflecting its ability to achieve very close results to those obtained through the resolution of the complex ILP within a negligible amount of time. Above and beyond, the proposed resource-sharing-based VNF placement scheme outperforms existing resource-sharing agnostic schemes by 15.6% and 14.7% in terms of bandwidth and CPU utilization respectively. [ABSTRACT FROM AUTHOR]

Middleboxes (i.e., firewall, cache, proxy, etc.) are hardware appliances designed to enforce security and performance policies. Being an integral part of today’s cloud and enterprise networks, these middleboxes are expensive, hard to manage and to maintain. Network function virtualization has emerged as a promising technology that replaces these hardware appliances by software ones known as virtual network functions (VNFs). Unlike hardware middleboxes, VNFs can be instantiated and deployed on virtual machines running on commodity servers which ensures their flexibility, manageability, cost-efficiency, and reduce their time-to-market. However, efficiently processing services through an ordered chain of VNFs, called service function chaining (SFC), is not trivial. It requires solving three inter-related sub-problems; the network functions (NFs) mapping sub-problem, the traffic routing sub-problem and the service scheduling sub-problem. This paper first highlights the existing interplay between the three sub-problems and then presents a formulation of the SFC scheduling (SFCS) which exploits interactions between NFs mapping onto VNFs, service scheduling and traffic routing. Given the complexity of the SFCS problem, we present a novel primal–dual decomposition using column generation that solves exactly a relaxed version of the problem and can serve as a benchmark approach. We enhance our solution methodology with a diversification technique to help improve the quality of the obtained solutions. We evaluate numerically our method and show that it can attain optimal solutions substantially faster. Finally, we present several engineering insights for improving the network performance. [ABSTRACT FROM PUBLISHER]

Traditionally, service-specific network functions (NFs) (e.g., Firewall, intrusion detection system, etc.) are executed by installation-and maintenance-costly hardware middleboxes that are deployed within a datacenter network following a strictly ordered chain. NF virtualization (NFV) virtualizes these NFs and transforms them into instances of plain software referred to as virtual NFs (VNFs) and executed by virtual machines, which, in turn, are hosted over one or multiple industry-standard physical machines. The failure (e.g., hardware or software) of any one of a service chain’s VNFs leads to breaking down the entire chain and causing significant data losses, delays, and resource wastage. This paper establishes a reliability-aware and delay-constrained (READ) routing optimization framework for NFV-enabled datacenter networks. READ encloses the formulation of a complex mixed integer linear program (MILP) whose resolution yields an optimal network service VNF placement and traffic routing policy that jointly maximizes the achieved respective reliabilities of supported network services and minimizes these services’ respective end-to-end delays. A heuristic algorithm dubbed Greedy- k -shortest paths (GSP) is proposed for the purpose of overcoming the MILP’s complexity and develop an efficient routing scheme whose results are comparable to those of READ’s optimal counterparts. Thorough numerical analyses are conducted to evaluate the network’s performance under GSP, and hence, gauge its merit; particularly, when compared to existing schemes, GSP exhibits an improvement of 18.5% in terms of the average end-to-end delay as well as 7.4% to 14.8% in terms of reliability. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of jointly constructing and scheduling forwarding trees in a wireless sensor network, each to collect measurements from a group of sensor nodes at a single sink node. The goal is to construct such trees that gather measurements in the most energy efficient manner and with minimal gathering latency. We assume transmissions (carrying measurements) on wireless links interfere with one another, and thus, appropriate link scheduling is required to manage interference. We refer to this problem as forwarding tree construction and scheduling (FTCS). Each tree may be constructed independently, and then, its links are scheduled. However, when all trees are combined together, the shortest and energy efficient schedule may not be guaranteed. Furthermore, a large number of possible forwarding trees for each group of sensors may be considered. Both problems of enumerating forwarding trees and scheduling links for those trees are hard combinatorial problems. This is compounded by the fact that the two problems must be solved jointly, to guarantee the selection of the best forwarding trees that, when their links are scheduled, guarantee a shortest energy efficient schedule. After highlighting the complexity of the FTCS problem, we present a novel primal-dual decomposition method using column generation. We also highlight several challenges we faced when solving the decomposed problem and present efficient techniques for mitigating those challenges. One major advantage of this paper is that it can serve as a benchmark for evaluating the performance of any low complexity method for solving the FTCS problem for larger network instances, where no known exact solutions can be found. [ABSTRACT FROM PUBLISHER]

Compressive data gathering (CDG) has emerged as a useful method for collecting sensory data in large scale sensor networks; this technique is able to reduce global scale communication cost without introducing intensive computation, and is capable of extending the lifetime of the entire sensor network by balancing the aggregation and forwarding load across the network. With CDG, multiple forwarding trees are constructed, each for aggregating a coded or compressed measurement, and these measurements are collected at the sink for recovering the uncoded transmissions from the sensors. This paper studies the problem of constructing forwarding trees for collecting and aggregating sensed data in the network under the realistic physical interference model. The problem of gathering tree construction and link scheduling is addressed jointly, through a mathematical formulation, and its complexity is underlined. Our objective is to collect data at the sink with both minimal latency and fewer transmissions. We show the joint problem is NP-hard and owing to its complexity, we present a decentralized method for solving the tree construction and the link scheduling subproblems. Our link scheduling subproblem relies on defining an interference neighbourhood for each link and co-ordinating transmissions among network links to control the interference. We prove the correctness of our algorithmic method and analyse its performance. Numerical results are presented to compare the performance of the decentralized solution with the joint model as well as prior work from the literature. [ABSTRACT FROM PUBLISHER]

Network virtualization is regarded as the pillar of cloud computing, enabling the multi-tenancy concept where multiple Virtual Networks (VNs) can cohabit the same substrate network. With network virtualization, the problem of allocating resources to the various tenants, commonly known as the Virtual Network Embedding problem, emerges as a challenge. Its NP-Hard nature has drawn a lot of attention from the research community, many of which however overlooked the type of communication that a given VN may exhibit, assuming that they all exhibit a one-to-one (unicast) communication only. In this paper, we motivate the importance of characterizing the mode of communication in VN requests, and we focus our attention on the problem of embedding VNs with a one-to-many (multicast) communication mode. Throughout this paper, we highlight the unique properties of multicast VNs and its distinct Quality of Service (QoS) requirements, most notably the end-delay and delay-variation constraints for delay-sensitive multicast services. Further, we showcase the limitations of handling a multicast VN as unicast. To this extent, we formally define the VNE problem for Multicast VNs (MVNs) and prove its NP-Hard nature. We propose two novel approach to solve the Multicast VNE (MVNE) problem with end-delay and delay variation constraints: A 3-Step MVNE technique, and a Tabu-Search algorithm. We motivate the intuition behind our proposed embedding techniques, and provide a competitive analysis of our suggested approaches over multiple metrics and against other embedding heuristics. [ABSTRACT FROM PUBLISHER]

The performance of wireless multihop networks depends on the achievable channel capacity for each transmission link as well as the level of spectrum spatial reuse in the network. For the latter one, successive interference cancellation (SIC) has emerged as an advanced PHY technique with the ability of decoding two or more overlapping signals and therefore allowing multiple concurrent transmissions. Effectively managing the transmission concurrency over the shared medium ensures good quality of transmission and therefore results in higher achievable transmission data rates. In this paper, we seek to understand the benefits of SIC and its interference management capabilities in a multi-rate multihop wireless network. To characterize the network performance under these characteristics, we follow a cross-layer design approach and formulate the joint routing and scheduling problem with rate control as a mixed integer linear program with the objective to maximize the minimum flow throughput. Given its large scale and combinatorial complexity, we follow a decomposition approach using column generation to solve the problem. However, the complexity of solving exactly the pricing subproblem limits the application of the model to very small size network instances. We develop one efficient greedy method for solving exactly the pricing subproblem as well as a simulated annealing based heuristic approach with very good performance. Our results indicate that SIC benefits strongly depend on the strength of the received signals. We show that transmission links with fixed higher data rates do not necessarily yield higher SIC gains because higher transmission rates result in sparser network topologies and thus less flexible routing. Larger networks with SIC capabilities and bitrate adaptation however are most effective in controlling the interference and improving the spatial reuse and thus reap the largest benefits with gains exceeding 20% over networks only with SIC capabilities or only with rate control. [ABSTRACT FROM AUTHOR]

Cloud Computing is becoming a mainstream paradigm, as organizations, large and small, begin to harness its benefits. This novel technology brings new challenges, mostly in the protocols that govern its underlying infrastructure. Traffic engineering in cloud data centers is one of these challenges that has attracted attention from the research community, particularly since the legacy protocols employed in data centers offer limited and unscalable traffic management. Many advocated for the use of VLANs as a way to provide scalable traffic management, however, finding the optimal traffic split between VLANs is the well known NP-Complete VLAN assignment problem. The size of the search space of the VLAN assignment problem is huge, even for small size networks. This paper introduce a novel decomposition approach to solve the VLAN mapping problem in cloud data centers through column generation. Column generation is an effective technique that is proven to reach optimality by exploring only a small subset of the search space. We introduce both an exact and a semi-heuristic decomposition with the objective to achieve load balancing by minimizing the maximum link load in the network. Our numerical results have shown that our approach explores less than 1% of the available search space, with an optimality gap of at most 4%. We have also compared and assessed the performance of our decomposition model and state of the art protocols in traffic engineering. This comparative analysis proves that our model attains encouraging gain over its peers. [ABSTRACT FROM PUBLISHER]

This paper addresses, in the context of wireless network design, the problem of optimally partitioning the spectrum into a set of nonoverlapping channels with nonuniform spectrum widths. While narrower bands split the total available spectrum into more nonoverlapping channels allowing more parallel concurrent transmissions, wider spectrum bands yield links with larger transport capacity. Thus, we model the combinatorially complex problem of joint routing, link scheduling, and variable-width channel allocation in both single and multirate multihop wireless networks as a mixed integer linear program, and present a solution framework using the column generation decomposition approach. Given the nature and complexity of the resulting dual subproblem, we propose heuristic methods for partitioning the spectrum and allocating resources to each active links, and hence obtain solutions for larger network instances. We present several numerical results and engineering insights suggesting both spectrum width and transmission rates as effective tunable knobs for combatting interference and promoting spatial reuse and thus achieving superior performance in multihop settings. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cross-layer design framework for the joint problem of coding-aware routing and scheduling in WiMAX-based mesh networks with unicast sessions. The model attempts to maximize the system throughput by exploiting opportunistic coding opportunities through appropriate routing and by achieving efficient spectrum reuse through appropriate link scheduling. We assume centralized scheduling at the base station and focus on minimizing the total schedule length to satisfy a certain traffic demand. Minimizing the schedule length is equivalent to maximizing the system throughput. We present a linear programming optimization model for the joint problem, which relies on the enumeration of all possible schedules. Given its complexity, we decompose the problem using a column generation approach. Our numerical results show that significant gains may be achieved when network coding is incorporated into the design. We compare the performance with that of a joint coding-oblivious model with and without transmission power control. [ABSTRACT FROM AUTHOR]

The recent Ethernet Ring Protection (ERP) method brings new challenges into the design of next generation Ethernet carrier networks. This letter addresses one of the design challenges that may confront a network operator in its migration to provide ERP capabilities over an existing network. The objective of the design is to properly allocate network resources to maximize the service provider's revenue given the per-link deployed capacity. We formulate this problem of resource allocation as an optimization model with the objective of maximizing the network flow using the well-known max-min approach. Our proposed model ensures fairness among the admissible flows and the design of a proper protection plan to survive against any single link failure. Numerical results show that the proposed design approach can increase the overall network flow by up to 44.7% in comparison to an arbitrarily designed ERP network while it allocates bandwidth 29.3% more fairly among the sessions. [ABSTRACT FROM PUBLISHER]

Abstract: Vehicular ad hoc networks (VANETs) enable vehicles to communicate with each other (V2V) as well as with roadside infrastructure units (V2I). These units provide different services such as driver information systems and Internet access. The high speed and high mobility of vehicles make it very challenging to establish and maintain a connection to these units. We introduce a new protocol which uses the characteristics of vehicle movements to predict the future behavior of vehicles, and to select a route with the longest lifetime to connect to the wired network. The proposed protocol aims at spreading the advertisement messages through multi-hops without flooding the network and performing seamless handovers. The proposed protocol is simulated by considering mobility scenarios, generated by the MOVE tool, in the ns-2 simulator tool. The simulation results show that the proposed scheme increases the packet delivery ratio and decreases the packet delay and overhead. [Copyright &y& Elsevier]

This paper describes a new vulnerability for the IEEE 802.11 protocol and studies its impact on degrading the performance of ad hoc networks. A host that exploits this new simple, but practical, vulnerability could cause devastating effects on the proper operation of the network protocols and hence severely degrade the performance. In this work, a misbehaving node fully cooperates by forwarding packets for other nodes and completely adheres to the proper selection of backoff intervals; however, it maliciously forces the forwarding operation to fail in order to either disrupt the route discovery process or to cause damage to existing flows routed though that node. As a result, the medium around the misbehaving node will be less congested and hence the node will obtain an increased unfair access to the channel. We use network simulations to show that such malicious misbehaviors have devastating effect on demoting the network performance and disrupting the protocol functioning. Hence, necessary extensions for existing detection systems are required to mitigate the effects of these new vulnerabilities. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper studies the interplay between network coding and spatial reuse in wireless mesh networks. We present a method that attempts to maximize the system performance by exploiting effectively (and not greedily) coding opportunities through appropriate routing and achieving efficient spectrum reuse through opportunistic link scheduling. We show that judiciously selecting coding structures requires proper transmission power allocation to better manage cumulative interference in the network, and thus yield better spectrum spatial reuse and effective multi-hop system throughput. We present an optimization model for this complex design problem, which relies on the enumeration of all possible schedules and decompose it into subproblems which we can solve more efficiently. Our numerical results indicate that optimal joint coding and scheduling with proper power allocation yields a performance enhancement of more than 10% over that with maximal power transmission and more than 45% enhancement over a coding oblivious design model. Our results also revealed that network coding has only marginal benefits (∼ 6%) in a dense network and that in such networks managing interference through proper power allocation yields very good performance. [ABSTRACT FROM PUBLISHER]

We investigate the problem of flexible spectrum access in multihop wireless networks. We assume radios that are capable of transmitting on channels of contiguous frequency bands and which do not require any sophisticated processing. Because these radios can flexibly configure their transmissions anywhere in the available frequency band, the spectrum becomes vulnerable to fragmentation and interference. We consider the joint problem of routing, link scheduling and spectrum allocation where scheduling feasibility is considered under the physical interference (SINR) constraint. We present a primal-dual decomposition for this complex optimization problem based on column generation. We show that obtaining the optimal solution to this problem is computationally not feasible, except for very small networks. We thus adopt a two-fold method to circumvent the complexity while yielding practical solutions. First, we relax the SINR constraint and use a simplified graph-based model for the interference. Second, we use a simulated annealing (SA) approach to solve the dual subproblem. Our SA approach however is augmented with an SINR feasibility check. Our results confirm that the primal-dual decomposition method using SA substantially reduces the computation time and achieves near optimal solutions. The results also reveal that substantial improvement in network performance is obtained with flexible spectrum assignment which results from its capability of better managing the interference in the network. [ABSTRACT FROM PUBLISHER]