A machine learning application for latency prediction in operational 4G networks

Measuring performance on Internet is always challenging. When it comes to the mobile networks, the variety of technology characteristics coupled with the opaque network configuration make the performance evaluation even a more difficult task. Latency is one of the aspects having the largest impact on the performance and on the end users' Quality of Experience. In this paper, we present a machine learning approach that, exploiting real mobile network data on the end user, try to predict the latency in a real operational network. We consider a large-scale dataset with more than 238 million latency measurements coming from 3 different commercial mobile operators. The presented methodology flattens the RTT values into several bins, turning the latency prediction problem to a multi-label classification problem. Then, three well-known supervised algorithms are exploited to predict the latency. The obtained results highlight the importance of representative dataset from operational network. It calls for further improvements on the algorithm selection, tuning, and their predictive capabilities

Efficient access of mobile flows to heterogeneous networks under flash crowds

Future wireless networks need to offer orders of magnitude more capacity to address the predicted growth in mobile traffic demand. Operators to enhance the capacity of cellular networks are increasingly using WiFi to offload traffic from their core networks. This paper deals with the efficient and flexible management of a heterogeneous networking environment offering wireless access to multimode terminals. This wireless access is evaluated under disruptive usage scenarios, such as flash crowds, which can mean unwanted severe congestion on a specific operator network whilst the remaining available capacity from other access technologies is not being used. To address these issues, we propose a scalable network assisted distributed solution that is administered by centralized policies, and an embedded reputation system, by which initially selfish operators are encouraged to cooperate under the threat of churn. Our solution after detecting a congested technology, including within its wired backhaul, automatically offloads and balances the flows amongst the access resources from all the existing technologies, following some quality metrics. Our results show that the smart integration of access networks can yield an additional wireless quality for mobile flows up to thirty eight percent beyond that feasible from the best effort standalone operation of each wireless access technology. It is also evidenced that backhaul constraints are conveniently reflected on the way the flow access to wireless media is granted. Finally, we have analyzed the sensitivity of the handover decision algorithm running in each terminal agent to consecutive flash crowds, as well as its centralized feature that controls the connection quality offered by a heterogeneous access infrastructure owned by distinct operators

A Multi-Objective Approach for a Multihoming Load Balancing Scheme in WHN

The telco operators face up to challenges related to the need of ensuring a quality of service to the user in a planning, maintenance and resource allocation in their complex networks. These challenges are directly related with the need to ensure an user’s service with a good level of quality in a highly dynamic environment in terms of changes in the radio access technologies, growth in the number of mobile users, technical requirements of the new services and applications, and the possibility to connect to different networks at the same time, among others. In this paper, we address the problem of the user’s service allocation into the different feasible networks in order to reduce the network overloading. We present a multihoming load balancing scheme that allows the re-allocation of services according to their QoS requirements and the availability of network resources. We propose a multi-objective optimization model of this problem together with an evolutionary algorithm to solve it. Through simulation in different scenarios, we show that our algorithm is efficient, sensitive, scalable and provides optimal solutions

Future Trends and Challenges for Mobile and Convergent Networks

Some traffic characteristics like real-time, location-based, and community-inspired, as well as the exponential increase on the data traffic in mobile networks, are challenging the academia and standardization communities to manage these networks in completely novel and intelligent ways, otherwise, current network infrastructures can not offer a connection service with an acceptable quality for both emergent traffic demand and application requisites. In this way, a very relevant research problem that needs to be addressed is how a heterogeneous wireless access infrastructure should be controlled to offer a network access with a proper level of quality for diverse flows ending at multi-mode devices in mobile scenarios. The current chapter reviews recent research and standardization work developed under the most used wireless access technologies and mobile access proposals. It comprehensively outlines the impact on the deployment of those technologies in future networking environments, not only on the network performance but also in how the most important requirements of several relevant players, such as, content providers, network operators, and users/terminals can be addressed. Finally, the chapter concludes referring the most notable aspects in how the environment of future networks are expected to evolve like technology convergence, service convergence, terminal convergence, market convergence, environmental awareness, energy-efficiency, self-organized and intelligent infrastructure, as well as the most important functional requisites to be addressed through that infrastructure such as flow mobility, data offloading, load balancing and vertical multihoming.Comment: In book 4G & Beyond: The Convergence of Networks, Devices and Services, Nova Science Publishers, 201

Performance Evaluation of TCP Multihoming for IPV6 Anycast Networks and Proxy Placement

In this thesis, the impact of multihomed clients and multihomed proxy servers on the performance of modern networks is investigated. The network model used in our investigation integrates three main components: the new one-to-any Anycast communication paradigm that facilitates server replication, the next generation Internet Protocol Version 6 (IPv6) that offers larger address space for packet switched networks, and the emerging multihoming trend of connecting devices and smart phones to more than one Internet service provider thereby acquiring more than one IP address. The design of a previously proposed Proxy IP Anycast service is modified to integrate user device multihoming and Ipv6 routing. The impact of user device multihoming (single-homed, dual-homed, and triple-homed) on network performance is extensively analyzed using realistic network topologies and different traffic scenarios of client-server TCP flows. Network throughput, packet latency delay and packet loss rate are the three performance metrics used in our analysis. Performance comparisons between the Anycast Proxy service and the native IP Anycast protocol are presented. The number of Anycast proxy servers and their placement are studied. Five placement methods have been implemented and evaluated including random placement, highest traffic placement, highest number of active interface placements, K-DS placement and a new hybrid placement method. The work presented in this thesis provides new insight into the performance of some new emerging communication paradigms and how to improve their design. Although the work has been limited to investigating Anycast proxy servers, the results can be beneficial and applicable to other types of overlay proxy services such as multicast proxies

Managed access dependability for critical services in wireless inter domain environment

The Information and Communications Technology (ICT) industry has through the last decades changed and still continues to affect the way people interact with each other and how they access and share information, services and applications in a global market characterized by constant change and evolution. For a networked and highly dynamic society, with consumers and market actors providing infrastructure, networks, services and applications, the mutual dependencies of failure free operations are getting more and more complex. Service Level Agreements (SLAs) between the various actors and users may be used to describe the offerings along with price schemes and promises regarding the delivered quality. However, there is no guarantee for failure free operations whatever efforts and means deployed. A system fails for a number of reasons, but automatic fault handling mechanisms and operational procedures may be used to decrease the probability for service interruptions. The global number of mobile broadband Internet subscriptions surpassed the number of broadband subscriptions over fixed technologies in 2010. The User Equipment (UE) has become a powerful device supporting a number of wireless access technologies and the always best connected opportunities have become a reality. Some services, e.g. health care, smart power grid control, surveillance/monitoring etc. called critical services in this thesis, put high requirements on service dependability. A definition of dependability is the ability to deliver services that can justifiably be trusted. For critical services, the access networks become crucial factors for achieving high dependability. A major challenge in a multi operator, multi technology wireless environment is the mobility of the user that necessitates handovers according to the physical movement. In this thesis it is proposed an approach for how to optimize the dependability for critical services in multi operator, multi technology wireless environment. This approach allows predicting the service availability and continuity at real-time. Predictions of the optimal service availability and continuity are considered crucial for critical services. To increase the dependability for critical services dual homing is proposed where the use of combinations of access points, possibly owned by different operators and using different technologies, are optimized for the specific location and movement of the user. A central part of the thesis is how to ensure the disjointedness of physical and logical resources so important for utilizing the dependability increase potential with dual homing. To address the interdependency issues between physical and logical resources, a study of Operations, Administrations, and Maintenance (OA&M) processes related to the access network of a commercial Global System for Mobile Communications (GSM)/Universal Mobile Telecommunications System (UMTS) operator was performed. The insight obtained by the study provided valuable information of the inter woven dependencies between different actors in the delivery chain of services. Based on the insight gained from the study of OA&M processes a technological neutral information model of physical and logical resources in the access networks is proposed. The model is used for service availability and continuity prediction and to unveil interdependencies between resources for the infrastructure. The model is proposed as an extension of the Media Independent Handover (MIH) framework. A field trial in a commercial network was conducted to verify the feasibility in retrieving the model related information from the operators' Operational Support Systems (OSSs) and to emulate the extension and usage of the MIH framework. In the thesis it is proposed how measurement reports from UE and signaling in networks are used to define virtual cells as part of the proposed extension of the MIH framework. Virtual cells are limited geographical areas where the radio conditions are homogeneous. Virtual cells have radio coverage from a number of access points. A Markovian model is proposed for prediction of the service continuity of a dual homed critical service, where both the infrastructure and radio links are considered. A dependability gain is obtained by choosing a global optimal sequence of access points. Great emphasizes have been on developing computational e cient techniques and near-optimal solutions considered important for being able to predict service continuity at real-time for critical services. The proposed techniques to obtain the global optimal sequence of access points may be used by handover and multi homing mechanisms/protocols for timely handover decisions and access point selections. With the proposed extension of the MIH framework a global optimal sequence of access points providing the highest reliability may be predicted at real-time