This paper underscores the crucial role of video anonymization in smart ports, were data privacy and security hold critical importance. It introduces the Matrix Platform, specifically designed for smart environments, and highlights its strong video anonymization capabilities. The platform employs advanced Video Anonymization techniques to effectively balance the preservation of data confidentiality with the enhancement of port security. Furthermore, the paper discusses how object detection and anonymization methods are strategically employed to protect sensitive information while still allowing access to critical operational details such as cargo and vessel types. Emphasis is placed on video anonymization's pivotal role in strengthening port security by concealing high-value assets and minimizing the risk of exposing sensitive data. By integrating the Matrix Platform, ports gain the capability to proactively manage security risks, safeguard assets, and secure information. This adaptable platform can be deployed in both Edge and Cloud environments, ensuring alignment with the specific needs of smart ports, with a primary focus on data anonymization. In conclusion, as the port industry continues to evolve, this paper asserts that the adoption of video anonymization techniques is fundamental for future growth and development, providing assurance of privacy and security in this dynamic landscape.

This paper presents an approach to autonomous IoT device lifecycle management for our developed Matrix IoT platform. We discuss our approach for zero touch onboarding, IoT device failure, device end-of-life offboarding and SLAs to support device lifecycle management. We collected timings on the key stages of our proposed onboarding process. The total onboarding time takes on average 6.4 seconds to onboard a device. Therefore, when scaled to many hundreds of devices, there is a very significant time saving benefit to onboarding devices automatically, along with the benefits of reducing human error.

This paper investigates architectural and capacity issues associated with analogue and digital radio over fibre fronthaul for MIMO in 5G cellular systems. The capacity of both systems is evaluated in terms of a static system deployment and also with varying traffic load. The results show that in a leased line scenario, the analogue systems offer an opportunity to reduce the cost of fibre infrastructure by more than 93% due to the more efficient use of bandwidth. but since the ARoF equipment is currently more expensive than the DRoF equivalent, there is a trade-off between CAPEX and OPEX for a given deployment.

Big Data technologies and tools have being used for the past decade to solve several scientific and industry problems, with Hadoop/YARN becoming the “de facto” standard for these applications, although other technologies run on top of it. As any other distributed application, those big data technologies rely heavily on the network infrastructure to read and move data from hundreds or thousands of cluster nodes. Although these technologies are based on reliable and efficient distributed algorithms, there are scenarios and conditions that can generate bottlenecks and inefficiencies, i.e., when a high number of concurrent users creates data access contention. In this paper, we propose a novel network topology called Multi-Layer-Mesh and a path switching algorithm based on SDN, that can increase the performance of a big data cluster while reducing the amount of utilized resources (network equipment), in turn reducing the energy and cooling consumption. A thorough simulation-based evaluation of our algorithms shows an average improvement in performance of 31.77% and an average decrease in resource utilization of 36.03% compared to a traditional Spine-Leaf topology, in the selected test scenarios.

The global view enabled by a Software Defined Network (SDN) architecture allows us to observe the contribution of each congested router to the overall Mean Opinion Score (MOS) degradation of a VoIP service. Thus, when a number of routers in the path may add to the MOS degradation, the SDN controller can quantify the contribution from each router. This work presents the implementation of a network monitoring system for OpenFlow protocol aware enterprise VoIP networks. The presented solution enables network administrators and developers to access on demand information about intermediate packet loss and MOS for real-time applications. The main contribution of this work is an out-of-the-box architecture to enable users to find the exact location of quality degradation with a small operational cost.

Summary The identification of performance issues and the diagnosis of their root causes are time‐consuming and complex tasks, especially in clustered environments. To simplify these tasks, researchers have been developing tools with built‐in expertise for practitioners. However, various limitations exist in these tools that prevent their efficient usage in the performance testing of clusters (e.g. the need of manually analysing huge volumes of distributed results). In a previous work, we introduced a policy‐based adaptive framework (PHOEBE) that automates the usage of diagnosis tools in the performance testing of clustered systems, in order to improve a tester's productivity, by decreasing the effort and expertise needed to effectively use such tools. This paper extends that work by broadening the set of policies available in PHOEBE, as well as by performing a comprehensive assessment of PHOEBE in terms of its benefits, costs and generality (with respect to the used diagnosis tool). The performed evaluation involved a set of experiments in assessing the different trade‐offs commonly experienced by a tester when using a performance diagnosis tool, as well as the time savings that PHOEBE can bring to the performance testing and analysis processes. Our results have shown that PHOEBE can drastically reduce the effort required by a tester to do performance testing and analysis in a cluster. PHOEBE also exhibited consistent behaviour (i.e. similar time‐savings and resource utilisations), when applied to a set of commonly used diagnosis tools, demonstrating its generality. Finally, PHOEBE proved to be capable of simplifying the configuration of a diagnosis tool. This was achieved by addressing the identified trade‐offs without the need for manual intervention from the tester. Copyright © 2017 John Wiley & Sons, Ltd.

The Software Defined Networking (SDN) paradigm enables quick deployment of software controlled network infrastructures, however new approaches to system monitoring are required to provide network administrators with instant feedback on a network's health. This paper details the deployment of an SDN system architecture featuring the integration of a cloud-based, real-time log-analysis platform. The proposed architecture uses log data collected from host machines, OpenFlow switches and the SDN controllers in a non-invasive style. This work uses a commercially available correlation platform to provide network administrators with a real-time view of the network status and the approach is validated under two scenarios:network overload and a security attack.

Summary Nowadays, clustered environments are commonly used in high‐performance computing and enterprise‐level applications to achieve faster response time and higher throughput than single machine environments. Nevertheless, how to effectively manage the workloads in these clusters has become a new challenge. As a load balancer is typically used to distribute the workload among the cluster's nodes, multiple research efforts have concentrated on enhancing the capabilities of load balancers. Our previous work presented a novel adaptive load balancing strategy (TRINI) that improves the performance of a clustered Java system by avoiding the performance impacts of major garbage collection, which is an important cause of performance degradation in Java. The aim of this paper is to strengthen the validation of TRINI by extending its experimental evaluation in terms of generality, scalability and reliability. Our results have shown that TRINI can achieve significant performance improvements, as well as a consistent behaviour, when it is applied to a set of commonly used load balancing algorithms, demonstrating its generality. TRINI also proved to be scalable across different cluster sizes, as its performance improvements did not noticeably degrade when increasing the cluster size. Finally, TRINI exhibited reliable behaviour over extended time periods, introducing only a small overhead to the cluster in such conditions. These results offer practitioners a valuable reference regarding the benefits that a load balancing strategy, based on garbage collection, can bring to a clustered Java system. Copyright © 2016 John Wiley & Sons, Ltd.

Summary As part of the process to test a new release of an application, the performance testing team need to confirm that the existing functionalities do not perform worse than those in the previous release, a problem known as performance regression anomaly. Most existing approaches to analyse performance regression testing data vary according to the applied workload, which usually leads to the need for an extra performance testing run. To ease such lengthy tasks, we propose a new workload‐independent, automated technique to detect anomalies in performance regression testing data using the concept known as transaction profile (TP). The TP is inferred from the performance regression testing data along with the queueing network model of the testing system. Based on a case study conducted against two web applications, one open source and one industrial, we have been able to automatically generate the ‘TP run report’ and verify that it can be used to uncover performance regression anomalies caused by software updates. In particular, the report helped us to isolate the real anomaly issues from those caused by workload changes with an average F1 measure of 85% for the open source application and 90% for the industrial application. Such results support our proposal to use the TP as a more efficient technique in identifying performance regression anomalies than the state of the art industry and research techniques. Copyright © 2015 John Wiley & Sons, Ltd.

Modern computer applications, especially at enterprise-level, are commonly deployed with a big number of clustered instances to achieve a higher system performance, in which case single machine based solutions are less cost-effective. However, how to effectively manage these clustered applications has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution between each clustered application. Since then, many research efforts have been carried out to study effective load balancing algorithms which can control the workload based on various resource usages such as CPU and memory. The aim of this paper is to propose a new load balancing approach to improve the overall distributed system performance by avoiding potential performance impacts caused by Major Java Garbage Collection. The experimental results have shown that the proposed load balancing algorithm can achieve a significant higher throughput and lower response time compared to the round-robin approach. In addition, the proposed solution only has a small overhead introduced to the distributed system, where unused resources are available to enable other load balancing algorithms together to achieve a better system performance.

Using modelling to predict the performance characteristics of software applications typically uses Queueing Network Models representing the various system hardware resources. Leaving out the software resources, such as the limited number of threads, in such models leads to a reduced prediction accuracy. Accounting for Software Contention is a challenging task as existing techniques to model software components are complex and require deep knowledge of the software architecture. Furthermore, they also require complex measurement processes to obtain the model's service demands. In addition, solving the resultant model usually require simulation solvers which are often time consuming.

omputing servers generally have a narrow dynamic power range. For instance, even completely idle servers consume between 50% and 70% of their peak power. Since the usage rate of the server has the main influence on its power consumption, energy-efficiency is achieved whenever the utilization of the servers that are powered on reaches its peak. For this purpose, enterprises generally adopt the following technique: consolidate as many workloads as possible via virtualization in a minimum amount of servers (i.e. maximize utilization) and power down the ones that remain idle (i.e. reduce power consumption). However, such approach can severely impact servers' performance and reliability. In this paper, we propose a methodology to determine the ideal values for power consumption and utilization for a server without performance degradation. We accomplish this through a series of experiments using two typical types of workloads commonly found in enterprises: TPC-H and SPECpower ssj2008 benchmarks. We use the first to measure the amount of queries responded successfully per hour for different numbers of users (i.e. [email protected]) in the VM. Moreover, we use the latter to measure the power consumption and number of operations successfully handled by a VM at different target loads. We conducted experiments varying the utilization level and number of users for different VMs and the results show that it is possible to reach the maximum value of power consumption for a server, without experiencing performance degradations when running indi- vidual, or mixing workloads.

Bugs in a project, at any stage of Software life cycle development are costly and difficult to find and fix.Moreover, the later a bug is found, the more expensive it is to fix.There are static analysis tools to ease the process of finding bugs, but their results are not easy to filter out critical errors and is time consuming to analyze.To solve this problem we used two steps: first to enhance the bugs severity and second is to estimate the code quality, by Weighted Error Code Density metric.Our experiment on 10 widely used open-source Java applications automatically shows their code quality estimated using our objective metric.We also enhance the error ranking of FindBugs, and provide a clear view on the critical errors to fix as well as low priority ones to potentially ignore.

Current trends show a growing number of femtocell deployments, this in turn will lead to increased volumes of voice traffic being transmitted through fixed broadband access networks such as Digital Subscriber Line. In this paper the issue of maintaining call quality through the resource constraint expedited forwarding queue of DSLAMs is investigated. A quality based Call Admission Control and resource allocation mechanism is provided to avoid resource overloading and call quality degradation. The ITU-T's E-Model is used for call quality monitoring and a message exchange interface between the mobile and fixed networks which allows dynamic adjustment to network resources is described and simulated. The results show that high voice call quality can be maintained.

The increasing number of users demanding voice and data communication through cellular networks has driven the need for higher network throughput rates and lower latency. LTE femtocells address this pressing problem by offloading cellular service providers networks and increase both coverage and capacity for their users. Assuming a wired DSL backhaul for these femtocells, this paper shows simulations exploring a case where the DSLAM represents the main bottleneck when the cellular network operator and the DSL provider do not collaborate. This paper introduces the concept of Intermediary Mean Opinion Score which may be employed at femtocell gateways to isolate network problems and feed into customer experience management. We also propose and investigate a technique of mapping the human audio recency into the MOS calculation. Results are presented to illustrate the information that can be extracted from a lightweight monitor in the network.

This paper examines two specific aspects of resource management in Wireless Local Area Networks (WLANs)-Call Admission Control (CAC) and handling of Link Adaptation (LA) events. A self-consistent system to manage these for Voice over Internet Protocol (VoIP) over an IEEE 802.11 WLAN is presented. The proposed CAC scheme is based on the Endpoint Admission Control (EAC) paradigm, where the endpoints probe the network to determine if the call can be supported with acceptable Quality of Service (QoS). The proposed scheme was evaluated on an experimental testbed and test results show that correct admission decisions were made under various network configurations. The scheme also determines if LA has resulted in the system becoming congested and, if so, the voice codec of the handset which has undergone LA is adapted so as to restore the system to its earlier state, thereby alleviating the congestion. The proposed scheme was evaluated on the experimental testbed and test results show that the codec adaptation scheme was very effective at overcoming the effects of LA for VoIP over WLAN.

We propose a simple and cost effective approach for the optical generation and downstream transmission of a data modulated 60 GHz signal using a gain switched laser (GSL). Gain switching is achieved by driving the laser with a 15 GHz local oscillator combined with a 1.25 Gbps on-off keyed (OOK) data stream. The system was tested over a 3 km length of fibre and a 2 m radio link and showed good performance. Simulations were also carried out for investigating the impact of optical suppression of unwanted subcarriers on the system performance. The simulations were also performed at up to 15 Gbps and showed the possibility of using the proposed architecture at these high bit rates.

Ethernet passive optical networks (EPONs) have attracted considerable attention from the industry, as they offer a simple, highly flexible and cost-effective solution to the problem of providing broadband access to a customer. The authors present a new approach to bandwidth allocation in EPONs where the optical line terminator (OLT) has full control over the access mechanism. This results in much simpler optical network unit (ONU) architecture. It is shown that such an OLT-centric architecture offers full support for differentiated services and makes enforcement of service level agreements possible. Extensive simulation experiments show that bandwidth allocation algorithms deployed in such a centralised environment can deliver good performance in terms of average and maximum packet delay. The authors introduce two new algorithms that target SLA-aware EPONs and provide a good protection of offered quality of service against interference from other sources.

Abstract — This paper presents how SCTP can stall in multihomed scenarios during failover and under certain circumstances. A stall is where an SCTP end-point ceases to communicate for an extended period of time, but does not report any error to the upper layer. This paper presents two different sets of circumstances where a stall can occur: firstly when there is an underestimation of the Retransmission Time-Out (RTO) value for a redundant network path; and secondly when a network error occurs that causes only SACKs to be lost, which confuses the SCTP sender about which network path is operational. Solutions to both of these stalls are presented that include modifying the RTO value, applying Karn’s algorithm to path monitoring and ensuring the destination address selection policy for SACKs is changed. This paper also presents a mechanism to de-couple data acknowledgement and path monitoring when using multi-homed transport protocols, which should remove the ambiguity about path monitoring and offers a universal solution to the stall. I.

The seamless handover of streamed video in a WLAN with UDP as the transport layer is considered. The use of handover for stationary nodes in the case of network congestion is motivated. Next, the relationship between delay and loss in WLANs is studied, with the conclusion that delay can be used as an indicator of when loss is likely to occur. Delay can therefore be used as a basis of a handover scheme which can minimize loss. Such a handover scheme is proposed in which the client makes two simultaneous connections to the same server through two separate WLANs, and it is shown that the client can use the relative packet delay between the two streams to determine which network delivers the best performance; this information is then used to determine when to perform a handover. The proposed scheme is implemented and results are presented that show the successful handover of an RTP over UDP stream using this scheme in a live WLAN environment.

In future wireless and mobile environments it is likely that users will have access to multiple networks at the same time. Therefore there is a need to have mechanisms in place to decide which network is the most suitable for each user at each moment in time for every application that the user requires. We propose a user-centric solution where users choose the radio access network which meets their data transfer terms best. Naturally, each user wants timely quality data delivery at a low cost. In the radio environment data rates can never be guaranteed due to the unreliable nature of the radio links. The user network selection algorithm needs to predict the data rate on offer in each of the available networks and make the decision based on those predictions. This paper allows the user to select the network that will maximise the consumer surplus for non real-time data, while taking into account the delays

A novel technique for estimating the average delay experienced by an IP packet in cellular data networks with an SR-ARQ loop is presented. This technique uses the following input data: a statistical description of the radio channel, ARQ loop design parameters and the size of a transported IP packet. An analytical model is derived to enable a closed form mathematical estimation of this delay. To validate this model, a computer based simulator was built and tests showed good agreement between the simulation results and the model. This new model is of particular interest in predicting the packet delay for conversational traffic such as that used for VoIP applications.

This article presents objective and subjective testing results that assess the performance of the Quality-Oriented Adaptation Scheme (QOAS) when used for high quality multimedia streaming over local broadband IP networks. Results of objective tests using a QOAS simulation model show very efficient adaptation in terms of end-user perceived quality, loss rate, and bandwidth utilization, compared to existing adaptive streaming schemes such as LDA+, and TFRCP. Subjective tests confirm these results by showing high end-user perceived quality of the QOAS under various network conditions.

Passive optical networks (PON) are thought to be the next step in the development of access networks and providing broadband access in the "last mile" area. Ethernet PON (EPON) are gaining the most attention from industry as they offer a highly flexible, cost effective solution. In this paper, we present a new approach to the problem of optimal bandwidth allocation in EPON. We show that by moving all the access control functionality to the optical line terminator, a flexible solution could be achieved which offers full support for service level agreements and removes the burden of managing the configuration of every optical network unit. We include results of simulations that show that such an approach can deliver good performance in terms of average and maximum packet delay. We show that a novel Grant multiplexing scheme can significantly reduce jitter and end-to-end delay experienced by the high priority classes of traffic. To prove these points we present results of detailed experiments that were run on a C++ event driven simulator, that we have developed.

Many adaptive delivery mechanisms have been devised for streaming multimedia over best-effort IP networks, such as the Internet. Most of these adaptive schemes do not consider the user's perception of quality when making adaptations. We describe a perceptual quality adaptation algorithm (PQA) and prototype system architecture that uses knowledge of user perceived quality to make adaptation decisions using an optimum adaptation trajectory. This optimum adaptation trajectory indicates how encoding quality should be adapted (upgraded/downgraded) with respect to user perceived quality in response to rapidly fluctuating network conditions. We present simulation results that demonstrate the behavior of a perceptual quality adaptation algorithm.

A novel methodology is proposed for the analysis of the IP packet delay performance of SR-ARQ mechanisms in a generalized wireless system. A simulation model of the system including a novel channel model is described and results are obtained for a range of IP packet size. To demonstrated the efficacy of the methodology, the test scenario is tailored to the transmission of small packets containing real-time data carried over an EGPRS system. The results show that the use of a mean value for IP packet delay estimation is of limited use when small packets are considered.

Many adaptive delivery mechanisms have been devised for streaming multimedia over best-effort IP networks. Most of these adaptive schemes do not consider the user's perception of quality when making adaptations. We propose that an optimum adaptation trajectory exists which indicates how encoding quality should be adapted (upgraded/downgraded) with respect to user perceived quality in response to network conditions. This optimum adaptation trajectory can be used with any transmission adaptation policy. We describe a system architecture that uses knowledge of user perceived quality to make adaptation decisions and give an example of how this knowledge can be used to complement the sender-based adaptation algorithm, LDA.