Legacy Networks Research Articles

Technological Innovation and Quality Improvement in U.S. Broadband

The availability and quality of broadband service in the United States has been elevated as a salient policy issue by the migration of both households and firms to online activities in response to the Covid-19 pandemic. This paper investigates the effects of entry by non-incumbent broadband internet service providers (ISPs) making use of innovative, new non-legacy technologies (i.e., fiber and wireless) on residential broadband service quality offered by incumbent legacy (i.e., cable and DSL) ISPs.In 2019, the Federal Communications Commission released major corrections to its previously released Form 477 data on U.S. broadband deployment over the 2014-18 period that greatly reduces estimates of entry by new broadband ISPs into urban census blocks. Overall, entry into U.S. urban broadband markets falls by about half, compared to previously released, uncorrected data.Using data from this and multiple other sources, we build a rich panel data set covering all residential broadband services available, by ISP, technology and maximum advertised download speed for each of approximately six million populated U.S. census blocks between December 2014 and December 2018. In contrast with the previous literature, we utilize highly disaggregated data, control for evolving government subsidies to underserved census blocks, and relax strong statistical and economic assumptions maintained in prior work. This paper explores causal effects by estimating variants of a difference-in-differences model with a rich set of control variables. Our model controls for time-invariant unobservable heterogeneity using census block fixed effects. These allow us to identify the effects of entry of new ISPs on service quality in legacy networks serving urban residential customers in spatially disaggregated local markets. We also study reduced form models explaining ISP entry and assess the strength of candidate instruments to mitigate potential endogeneity caused by measurement error in counts of fixed wireless competitors, as well as possible unobserved time-varying census block heterogeneity relevant to ISP entry and exit.Our results suggest that entry into a 2014 “legacy duopoly” census block (about 40 percent of US census blocks were legacy—cable and DSL—terrestrial broadband duopolies in 2014) by other legacy ISPs had a large and statistically significant impact on improvements to maximum broadband quality offered to consumers by legacy ISPs serving a given block. Increased competition in local broadband markets from such “overbuilding” by established broadband providers seemed to result in significant quality improvements within a block.These results are consistent with a previous empirical literature that shows mixed, but generally positive effects of increased competition on product quality. More striking is the relatively small impact of increased competition on legacy ISP service quality in comparison to the apparent impacts of underlying time trends on legacy broadband speeds, trends that we believe primarily reflect dramatic technological changes over the 2014-18 period.

Affordable Broadband with Software Defined IPv6 Network for Developing Rural Communities

The software defined networking (SDN) paradigm with enhanced features of IPv6 offers flexible network management and better network visibility for enhancing overall network performance, network manageability, and security. Thus, along with the IPv6 network deployment worldwide, SDN migration has emerged worldwide, but network service providers suffer from different issues when migrating their existing legacy network into operable SDN and IPv6 enabled networks. In this paper, we investigate the affordability of broadband network services for the rural communities in the context of information and communication technology (ICT) infrastructure deployment throughout Nepal. During the phase of network transformation, it will be more challenging for the service providers of Nepal to have a proper choice of technologies to expand the network while considering the proper policy formulation, affordability, need of skilled human resources, deployment cost, and many other aspects. We also present the service provider affordability via energy optimization in software defined IPv6 network (SoDIP6) implementation that contributes to a reduction in organizational operational expenditure (OpEX). We perform an experimental analysis over an SoDIP6 network testbed and present a comparison of the annual energy and OpEX savings for network service providers. Our empirical analysis shows that an energy saving of 31.50% on switches and 55.44% on links can be achieved with an SoDIP6 network compared to a network with legacy devices and network management. Optimization on service provider network operational cost leads to sustainability and affordable services to both customers and service providers

SDN replaced deployment and real-time QoS provisioning based on network models

From industrial communications to real-time internet applications, end-to-end delay guarantee is one of the most important aspects of quality of service (QoS). As a new networking paradigm, software-defined networking (SDN) exposes an opportunity to provide this guarantee. In exploiting SDN, We can replace the legacy network devices to SDN forwarding units (SDN-FUs gradually. This paper focuses on the SDN replaced deployment problem, striving for providing real-time QoS provisioning in a network meanwhile. Utilising previous works originated from network calculus, we first propose the candidate nodes selection methods for upgrading legacy nodes to SDN-FUs and then present a routing algorithm located on SDN controller to direct the running of SDN-FUs. Via a simulation about a small network, we show that the delay of a flow passing through a network can reduce significantly with the usage of SDN.

Generic Validation Criteria and Methodologies for SDN Applications

Programmable control plane in software-defined networking (SDN), plays an essential role in the SDN architecture. The network function provided by the specialized hardware in a legacy network can be created in the form of software-based “SDN application” running on the controllers to manipulate entire network configurations. Therefore, the risk of having software bugs and errors in the SDN applications may threaten the normal operations of SDN networks. This paper presents systematic validation criteria and test cases based on the proposed novel methodologies for SDN application testing. The test framework can perform testbed build-up, generate desired packet sequences, and analyze results automatically. According to the results of a generic test suite, several issues are unveiled in the application under test (AUT). Some AUTs, which need to check all the incoming packets from OpenFlow switches, fail to meet the test criteria of burst packet-in and flow self-recycling. For most of the applications based on the Ryu controller, the evaluation results reveal that some are unable to recycle flow entries after they are unloaded. It is recommended that all flows populated by SDN applications must have timeout value specified to prevent unnecessary entries kept in the flow table.

Evolution of random access process: From Legacy networks to 5G and beyond

AbstractIn this paper, we discuss the random access procedures in legacy networks, long‐term evolution, LTE‐Advanced, and 5G networks. Random access is the first and incumbent step for connection establishment between base station/eNodeB/gNodeB and user equipment. Keeping in view its importance, there has been a regular thrive to improve the procedures of random access in communication networks. With the advent of new concepts such as machine‐type communication and Internet of Things, random access becomes extremely critical because huge number of devices try to connect to the network simultaneously. We present the evolution of random access process from legacy networks such as global system for mobile or wideband code division multiple access to 5G networks and beyond and their analysis. Simulations are performed in MATLAB to show various performance metrics such as access delay, total service time, and collision probability to demonstrate the pros and cons of one technique over another.

Software Defined Networking – Imposed Security Measures Over Vulnerable Threats and Attacks

Software defined networking (SDN), a new attempt in addressing the existing challenges in the legacy network architecture, is lime-lighted due to its simplified approach in managing the networks and its capability of programmability. In progressing with software defined networks implementation, security remains a high priority focus. The advantage of SDN itself opens a wide ground in posing new security threats and challenges. Focusing on the security of the SDN is a prime factor as it reflects on the growth of SDN technology implementation. This article focuses on the various existing security solutions available for SDN and the real challenge in securing the SDN providing the researchers a paved platform to work on further securing the networks. This article is designed with an introduction on SDN, its architecture, the available security solutions for the network, the leveraging threats and type of attack possibilities in SDN. This article concludes with the requirements of security factors and schemes in SDN.

AI-Enabled Future Wireless Networks: Challenges, Opportunities, and Open Issues

A plethora of demanding services and use cases mandate a revolutionary shift in the management of future wireless network resources. Indeed, when tight quality of service demands of applications are combined with increased complexity of the network, legacy network management routines will become unfeasible in 6G. Artificial Intelligence (AI) is emerging as a fundamental enabler to orchestrate the network resources from bottom to top. AI-enabled radio access and AI-enabled core will open up new opportunities for automated configuration of 6G. On the other hand, there are many challenges in AI-enabled networks that need to be addressed. Long convergence time, memory complexity, and complex behaviour of machine learning algorithms under uncertainty as well as highly dynamic channel, traffic and mobility conditions of the network contribute to the challenges. In this paper, we survey the state-of-art research in utilizing machine learning techniques in improving the performance of wireless networks. In addition, we identify challenges and open issues to provide a roadmap for the researchers.

A Role of Routing, Transport and Security Mechanisms in Information Centric Network

Legacy networks which were discovered in 1970’s suited better for olden day’s communication model where the network is host centric, but nowadays expectations from communication networks is changing and it is shifting from host centric to data centric. To suit recent expectations there is need of revolution in communication networks; Information Centric Network (ICN) is a new kind of network architecture evolving for future internet. This article introduces ICN and its prominent features and reviews the work done post architectural approaches in the areas of routing, transport and security specifically.

How Deep Should be the Depth of Convolutional Neural Networks: a Backyard Dog Case Study

The work concerns the problem of reducing a pre-trained deep neuronal network to a smaller network, with just few layers, whilst retaining the network’s functionality on a given task. In this particular case study, we are focusing on the networks developed for the purposes of face recognition. The proposed approach is motivated by the observation that the aim to deliver the highest accuracy possible in the broadest range of operational conditions, which many deep neural networks models strive to achieve, may not necessarily be always needed, desired or even achievable due to the lack of data or technical constraints. In relation to the face recognition problem, we formulated an example of such a use case, the ‘backyard dog’ problem. The ‘backyard dog’, implemented by a lean network, should correctly identify members from a limited group of individuals, a ‘family’, and should distinguish between them. At the same time, the network must produce an alarm to an image of an individual who is not in a member of the family, i.e. a ‘stranger’. To produce such a lean network, we propose a network shallowing algorithm. The algorithm takes an existing deep learning model on its input and outputs a shallowed version of the model. The algorithm is non-iterative and is based on the advanced supervised principal component analysis. Performance of the algorithm is assessed in exhaustive numerical experiments. Our experiments revealed that in the above use case, the ‘backyard dog’ problem, the method is capable of drastically reducing the depth of deep learning neural networks, albeit at the cost of mild performance deterioration. In this work, we proposed a simple non-iterative method for shallowing down pre-trained deep convolutional networks. The method is generic in the sense that it applies to a broad class of feed-forward networks, and is based on the advanced supervise principal component analysis. The method enables generation of families of smaller-size shallower specialized networks tuned for specific operational conditions and tasks from a single larger and more universal legacy network.

A new method for layer 2 loop prevention in software defined networks

Broadcast storm refers to the bandwidth saturation caused by broadcast traffic flows when a loop exists and it can quickly lead to the network failure. In legacy networks, spanning tree protocol (STP) is used to prevent loops in layer 2. This protocol is designed for distributed networks. However, for software defined networks (SDNs) as a new architecture for computer networks, it is necessary to have a new paradigm. In SDN architecture, control plane is decoupled from data plane and implemented centrally so it can be utilized to find a better solution using its global view. In this paper, a new method to prevent loop in SDNs is introduced and evaluated. The proposed method in comparison with STP, has better performance, because of blocking fewer switch ports and utilizing more capacity of the switches. The comprehensive simulation results showed the effectiveness of the proposed method.

High-speed Internet access and housing values

ABSTRACTA hedonic model is estimated that relates house values to high-speed Internet access while controlling for the potential endogeneity of Internet access. Results show that single-family homes with access to a 25 Mbps broadband connection have a price that is about $5,977, or 3%, more than similar homes in neighborhoods with 1 Mbps. The rural premium is lower at $5,099. A cost-benefit exercise on the viability of rural broadband shows that demand will generally not support private investment, but that the revenue gap from upgrading legacy networks could be readily covered by the Universal Service Fund and other public subsidies.

Reinforcement Learning Based Resource Management for Network Slicing

Network slicing to create multiple virtual networks, called network slice, is a promising technology to enable networking resource sharing among multiple tenants for the 5th generation (5G) networks. By offering a network slice to slice tenants, network slicing supports parallel services to meet the service level agreement (SLA). In legacy networks, every tenant pays a fixed and roughly estimated monthly or annual fee for shared resources according to a contract signed with a provider. However, such a fixed resource allocation mechanism may result in low resource utilization or violation of user quality of service (QoS) due to fluctuations in the network demand. To address this issue, we introduce a resource management system for network slicing and propose a dynamic resource adjustment algorithm based on reinforcement learning approach from each tenant’s point of view. First, the resource management for network slicing is modeled as a Markov Decision Process (MDP) with the state space, action space, and reward function. Then, we propose a Q-learning-based dynamic resource adjustment algorithm that aims at maximizing the profit of tenants while ensuring the QoS requirements of end-users. The numerical simulation results demonstrate that the proposed algorithm can significantly increase the profit of tenants compared to existing fixed resource allocation methods while satisfying the QoS requirements of end-users.

Joint Switch Upgrade and Controller Deployment in Hybrid Software-Defined Networks

To improve traffic management ability, Internet Service Providers (ISPs) are gradually upgrading legacy network devices to programmable devices that support Software-Defined Networking (SDN). The coexistence of legacy and SDN devices gives rise to a hybrid SDN. Existing hybrid SDNs do not consider the potential performance issues introduced by a centralized SDN controller: flow requests processed by a highly loaded controller may experience long tail processing delay; inappropriate multi-controller deployment could increase the propagation delay of flow requests. In this paper, we propose to jointly consider the deployment of SDN switches and their controllers for hybrid SDNs. We formulate the joint problem as an optimization problem that maximizes the number of flows that can be controlled and managed by the SDN and minimizes the propagation delay of flow requests between SDN controllers and switches under a given upgrade budget constraint. We show this problem is NP-hard. To efficiently solve the problem, we propose some techniques (e.g., strengthening the constraints and adding additional valid inequalities) to accelerate the global optimization solver for solving the problem for small networks and an efficient heuristic algorithm for solving it for large networks. The simulation results from real network topologies illustrate the effectiveness of the proposed techniques and show that our proposed heuristic algorithm uses a small number of controllers to manage a high amount of flows with good performance.

Dependable Fire Detection System with Multifunctional Artificial Intelligence Framework.

A fire detection system requires accurate and fast mechanisms to make the right decision in a fire situation. Since most commercial fire detection systems use a simple sensor, their fire recognition accuracy is deficient because of the limitations of the detection capability of the sensor. Existing proposals, which use rule-based algorithms or image-based machine learning can hardly adapt to the changes in the environment because of their static features. Since the legacy fire detection systems and network services do not guarantee data transfer latency, the required need for promptness is unmet. In this paper, we propose a new fire detection system with a multifunctional artificial intelligence framework and a data transfer delay minimization mechanism for the safety of smart cities. The framework includes a set of multiple machine learning algorithms and an adaptive fuzzy algorithm. In addition, Direct-MQTT based on SDN is introduced to solve the traffic concentration problems of the traditional MQTT. We verify the performance of the proposed system in terms of accuracy and delay time and found a fire detection accuracy of over 95%. The end-to-end delay, which comprises the transfer and decision delays, is reduced by an average of 72%.

Revitalizing DRX for enhanced mobile sleep modes

A flexible Discontinuous Reception (DRX) scheme is proposed to resolve the drawbacks of State-of-the-Art (SOTA) DRX scheme by eliminating the need of major timers and allowing Intra-Subframe Micro (ISM) sleep periods. The proposed new Timer Eliminating DRX (TE-DRX) scheme was tested and analyzed with traffic logs from live mobile network. This scheme can drastically reduce the active time of mobile devices by more than 75% and can thereby save at least 40% of energy to be used and improve battery life compared to practical technology limit of (SOTA) solution. It is shown that scheduling can be made relaxed. That is, the system is not forced to schedule data for (DRX) users in the first subframes of radio frames, and good performance does not require scheduling user data in consecutive subframes (like in case of short On-duration timers). Thereby it is possible to save energy even in heavily loaded systems and make very efficient (DRX) reality in legacy networks comparable to 5th Generation (5G) sleep mode proposals. Moreover, the proposed method can be considered as a possible extension of upcoming (5G) networks, as well.

Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN)

Software Defined Networking (SDN) has many advantages over a traditional network. The great advantage of SDN is that the network control is physically separated from forwarding devices. SDN can solve many security issues of a legacy network. Nevertheless, SDN has many security vulnerabilities. The biggest issue of SDN vulnerabilities is Distributed Denial of Service (DDoS) attack. The DDoS attack on SDN becomes an important problem, and varieties of methods had been applied for detection and mitigation purposes. The objectives of this paper are to propose a detection method of DDoS attacks by using SDN based technique that will disturb the legitimate user's activities at the minimum and to propose Advanced Support Vector Machine (ASVM) technique as an enhancement of existing Support Vector Machine (SVM) algorithm to detect DDoS attacks. ASVM technique is a multiclass classification method consisting of three classes. In this paper, we can successfully detect two types of flooding-based DDoS attacks. Our detection technique can reduce the training time as well as the testing time by using two key features, namely, the volumetric and the asymmetric features. We evaluate the results by measuring a false alarm rate, a detection rate, and accuracy. The detection accuracy of our detection technique is approximately 97% with the fastest training time and testing time.

Toward secure software-defined networks against distributed denial of service attack

The newly emerged software-defined networking (SDN) paradigm provides a flexible network management by decoupling the network control logic from the data plane, which could effectively resolve many security issues of legacy networks. One of such security issues is distributed denial of service (DDoS) attack, which is a rapidly growing network threat. This is usually performed on a target system to make an online service unavailable to the users. SDN can easily detect the DDoS attack due to the centralized control provisioning and network visibility. At the same time, the changes of fundamental architecture and the developments of various design entities pose a severe DDoS threat to the SDN platform. This paper presents a concise up-to-date review of security concerns of SDN, possible DDoS attack in individual layers of SDN and ongoing research efforts on SDN-enabled DDoS detection solutions. Based on the findings, an information distance-based flow discriminator framework has been discussed, which can discriminate the DDoS traffic during flash events, a similar looking legitimate traffic, in SDN environment. The information distance metric is used to describe the variations of traffic behavior of such events. The simulation results show that the information distance metric can effectively identify the DDoS traffic in comparison with other metrics with a higher detection rate. The proposed solution can detect the traffic at the edge switch so that the attack alert can be raised at the earliest.

Cross-Technology Communications for Heterogeneous IoT Devices Through Artificial Doppler Shifts

Recent years have seen major innovations in developing energy-efficient wireless technologies such as Bluetooth Low Energy (BLE) for Internet of Things (IoT). Despite demonstrating significant benefits in providing low power transmission and massive connectivity, hardly any of these technologies have made it to directly connect to the Internet. Recent advances demonstrate the viability of direct communication among heterogeneous IoT devices with incompatible physical (PHY) layers. These techniques, however, require modifications in transmission power or time, which may affect the media access control (MAC) layer behaviors in legacy networks. In this paper, we argue that the frequency domain can serve as a free side channel with minimal interruptions to legacy networks. To this end, we propose DopplerFi, a communication framework that enables a two-way communication channel between BLE and Wi-Fi by injecting artificial Doppler shifts, which can be decoded by sensing the patterns in the Gaussian frequency shift keying (GFSK) demodulator and Channel State Information (CSI). The artificial Doppler shifts can be compensated by the inherent frequency synchronization module and thus have a negligible impact on legacy communications. Our evaluation using commercial off-the-shelf (COTS) BLE chips and 802.11-compliant testbeds have demonstrated that DopplerFi can achieve throughput up to 6.5~Kbps at the cost of merely less than 0.8% throughput loss.

Optimizing the network edge for flexible service provisioning

The virtualization of network resources provides unique flexibility in service provisioning in most levels of the network stack. Softwarization of the network control and operation (SDN) is a key enabler of that development. Starting from the network core, SDN is a dominant trend in the evolution of network architectures with increased emphasis recently on the network edge. I will present some recent results in this area starting with a study on migration from legacy networking to SDN enabled network modules. The tradeoff between the benefits of SDN upgrades and the cost of deployment is addressed and captured by an appropriate sub-modular function that allows to optimize the penetration pace of the technology. Validation on some real world network topologies and traffic matrices will be presented as well. Then we move our attention to the network periphery. A wireless multi-hop extension at the network edge is considered and the problem of enabling SDN is addressed via replication of SDN controllers. The delay constraints of the controlled data-path elements is appropriately modeled and the problem of locating the controllers is addressed via optimization and a proof-of concept implementation. An alternate approach is considered then for the wireless network where we assume coexistence of SDN enabled components with network islands operating under distributed adhoc routing protocols. The trade-off of the coexistence is studied and the impact of SDN penetration is evaluated. Some paradigms of collaborative network services are presented finally as they are enabled by the above architectural evolution.

Mitigating attacks in software defined networks

Future network innovation lies in software defined networking (SDN). This innovative technology has revolutionised the networking world for half a decade and contributes to transform legacy network architectures. This transformation blesses the networking world with improved performance and quality of service. However, security for SDN remains an afterthought. In this paper we present a detailed discussion of some of the attacks possible in SDN and techniques to deal with the attacks. The threat model will consider some significantly vulnerable areas in SDN which can lead to severe network security breaches. In particular, we describe different attacks such as attacks on the Controller, attacks on networking devices, attacks exploiting the communication links between the control plane and the data plane and different types of topology poisoning attacks. We then propose techniques to deal with some of the attacks in SDN. We make use of northbound security application on the Controller and OpenFlow agents in the networking devices for enforcing security policies in the data plane. The security application is used for specification and storage of the security policies and to make decisions on the enforcement of security policies to deal with different types of attacks. We will describe the prototype implementation of our approach using ONOS Controller and demonstrate its effectiveness against different types of attacks.