Assessing Network Service Profitability: Modeling From Market Science Perspective

Network service providers regularly conduct network planning and upgrade processes to keep their businesses profitable. The effectiveness of a network upgrade/planning decision is intrinsically tied to the ability of a provider to retain and grow its customer population. This paper examines the crucial linkage between network performance, customer satisfaction and profitability of network service, and presents an analytical modeling approach from market science perspective. We derive a generalized forecasting model that projects service profitability from the underlying network service infrastructure and the subscriber population. Through simulation studies and analysis, we show how such approach captures key factors and trends influencing service profitability and how it can significantly improve current network planning and upgrade processes.     

Being proactive — analytics for predicting customer actions

Customers should be at the heart of most businesses, and in particular service providers such as BT. In order to serve our customers better, we regularly introduce reliable processes and procedures to improve interaction with our customers, which is known as customer relationship management. Typically, organisations collect and keep large volumes of customer data as part of their processes. Analysis of this data by business users often leads to discovery of valuable patterns and trends that otherwise would go unnoticed and that can lead to prioritisation of decisions on future investments. Current tools available to business users are limited to visualisation and reporting of data. What is needed is modelling customer behaviours to be able to build future scenarios. More advanced tools and techniques have been available for a number of years but have not been developed for the business community due to the level of expertise required to use them. In this paper we present a number of tools and techniques developed for business users to perform advanced analysis on customer data. The tools can be used to perform sensitivity analysis, what-if analysis and impact analysis, all of which are aimed at prediction and simulation of future customer actions. The paper also covers application of the tools to real customer data and reports on some of the results obtained.     

A risk-driven security analysis method and modelling language

The BT Security Research Centre has defined and continues to develop a modelling language and method for representing and analysing ICT security requirements. The language is used to create a model that serves as a medium for communication between consultant and customer, a guide in making decisions, and the basis of a specification for implementing a solution. Three sub-models deal with business and technical requirements of the ICT system; threats, vulnerability and risks; and security measures and processes. The modelling process is iterative, with decisions being driven by optimisation of business value, trading off risk against cost. This paper focuses on aspects of the method dealing with assessment of risk and analysis of requirements for operational risk management.     

Operational risk analysis in business processes

The operational continuity of a business process is an important performance indicator that contributes to the perceived quality of service delivery, hence it is important to understand and monitor the underlying issues that can affect the performance of the process. These issues might have been foreseen at the beginning of the process design and deployment phase, or might have emerged during the execution of the process, and must be viewed as risk threats to the business process. In most cases risk is only considered from the project management angle or from financial, market, insurance and other general business perspective. Operational risk at service provision level receives little attention and thus there is a need to develop methodologies and tools to identify and analyse business operational risks. The authors concentrate on operational risk for business process management by introducing a novel way for applying risk assessment frameworks at the process activity level. The paper briefly reviews existing risk frameworks and selects the COSO framework as the most appropriate for business processes. This framework is modified in order to address and evaluate the main elements of business processes. It defines a statistical approach towards operational risk assessment by quantifying risk factors in each activity within a business process for service provision. A risk forecast is produced for each activity, and for the whole process, to model associated uncertainties and to contribute in identifying the risk factors that affect the business process objectives. To demonstrate the framework, it is applied to a hypothetical process involving setting up a network service. These results help to advise on which risk factors need higher attention in order to achieve successful process fulfilment.     

Linearized Model of Object Caching and Heuristic Solution

Object-oriented (OO) technologies have become widely adopted in enterprise applications due to the additional functionality and flexibility they provide to these applications. At the same time, however, OO technologies also require significant amounts of computational power to support, greatly impacting the performance and scalability of such applications. A very popular solution to mitigate this problem is object caching. In this paper, we show how the application of object caching maps into an optimization problem. In particular, we focus on the design-time decision of determining which objects should be candidates for caching. Choosing the cacheable objects is an important decision since it can have a significant impact on application performance. We formulate this problem as a linear integer program and present a heuristic solution approach. We also demonstrate, through a set of experiments, that our heuristic provides solutions that are reasonably close to optimal. Our contribution is a model and an efficient solution approach for this model that can help application developers to make more informed cacheability decisions and thereby improve application performance and scalability.     

Standardized active measurements on a tier 1 IP backbone

Synthetic or active measurements are often used to characterize IP performance; however, it is rare to find them used to resolve problems in an operational setting. We show that the active monitoring system in the AT&T IP backbone provide's a comprehensive view of network performance that is complementary to traditional element level monitoring, making it an integral part of network management. This paper discusses the design and implementation of these active measurements in the network. We continuously monitor "path-level" performance metrics such as round-trip delay, loss, jitter, and reordering events to proactively detect impairments. Our system relies on the promotion of key metrics to the operational displays, while maintaining a rich set of statistics for analyzing rare and unforeseen events. This timely information enables us to react,quickly to performance degradation, avoiding any sustained effect on customer applications. The results also help us understand the network's ability to support time-sensitive application performance. Selected "interesting" events observed are presented, including detection of degradation caused by low-level bit errors on a physical link, detection of route changes on the network and their impact on real-time applications, and finally detection of reordering caused by forwarding loops.     

Using assurance models to aid the risk and governance life cycle

In this paper we describe an enterprise assurance model allowing many layers of the enterprise architecture, from the business processes, supporting applications and the IT infrastructure and operational processes, to be represented and related from a control and risk perspective. This provides a consistent way of capturing and relating the risk views for the various stakeholders within the organisation. At the lower level we use assurance models to provide automated testing of controls and policies, and at the higher level these results are related across the enterprise architecture. This enables a repository for manual and automated test results that can be used to derive different (but consistent) views for the various stakeholders.     

How to price Internet access for disloyal users under uncertainty

It has recently (Trinh 2008; Biczók et al. 2008) been demonstrated that customer loyalty can have a significant impact on Internet service provider (ISP) pricing. However, the results in those works are valid only under the assumption of complete information, i.e., both the ISPs and the customers fully know about each others’ decisions; the question of how Internet access prices are set by the ISP for disloyal users in uncertain circumstances is still largely unsolved. In this paper, we provide a game-theoretic framework to understand the impacts of customer loyalty on ISP price setting under uncertainty. The contribution of the paper is threefold. Firstly, we provide an empirical analysis of the customer loyalty issue by carrying out a survey for the Hungarian ISP market and combine the results with other European ISP markets. Secondly, we model ISPs’ uncertain decisions by using Bayesian games. Based on our game theoretic model, we quantify the effects of uncertainty on ISPs’ price setting and derive strategies to optimize ISPs’ profits under these uncertain conditions. After that, we generalize the results to mixed strategy scenarios. Finally, we develop a simulation tool to validate the theoretical results and to demonstrate our novel loyalty models. We argue that our findings can motivate researchers to incorporate a finer-grained user behavior model involving customer loyalty in their investigations of such interactions.     

Strategic e-Business Decision Analysis Using the Analytic Network Process

The rapid global deployment of electronic business (e-business) and information systems has required managers to make decisions that seek to balance technical factors with strategic business goals. This research utilizes the analytic network process (ANP) to provide insight into optimum-seeking decision processes by managers, as investments are made to utilize e-commerce technologies. The nonlinear network approach of ANP was used to study the "systems with feedback" where the e-commerce strategy may both dominate and be dominated, directly and indirectly, by the business-level strategy. This study analyzes e-business decisions in organizations, based on management heuristics and perceptions of expected contributions of e-commerce strategies, as well as the business-level strategies. The ANP research methodology process is employed since it is well suited for the study of a multi-attribute decision problem to explore qualitative and quantitative preferences of top managers in independent, nondiversified firms involved in e-business. ANP is used to model decision complexities involved in integrating e-commerce innovation into the overall strategic planning of firms. Optimal e-business strategies are chosen by using systems-with-feedback, where interdependencies between four virtual e-commerce domains and two generic business level strategies are explored. This study obtained significant results and identified several important avenues for further research. Implications for theory and research are discussed.     

An overview of intelligent control systems in cement plants: shop floor to boardroom

This work has attempted to give a brief overview of the power and benefits of intelligent integrated management systems. ICSs monitor and cover the whole factory from shop floor to boardroom, giving all plant personnel appropriate information and control. The power of the ICS is the ability to recognize and consolidate a whole variety of various process, operational, and management and governmental factors that allow the decision makers in plants to make better or optimal decisions with regard to their production, profitability, and whatever other goals that are important to them. Some of the benefits to ICS are better-informed staff, improved operational control, and better decision making, all of which affect the bottom line of the business to some degree. This includes higher throughput, consistent quality, less down time, and other benefits, such as better training and fast detection of problems, which are not easy to qualify or quantify. In general, the end user cannot operate as efficiently without such systems.     

On optimal trajectory for the multi-period evolution of FTTx networks

Telecommunication Systems - We propose a business/cost model for long-period changes of customer demands in FTTx networks. We show how to exploit this model in the formulation of a MIP optimization...     

自动拨测在集团客户短信业务网络监控中的应用研究

从集团客户短信业务网络特点出发,总结其网络监控的难点,提出利用自动拨测原理进行短信业务的端到端网络性能监控.通过搭建短信业务自动拨测系统,对短信业务网络进行轮询测试,获取端到端网络性能质量数据,能够在主动监控、故障预处理、故障定位、业务入网及网络调整后业务测试等方面发挥较好的作用,从而更好的监测网络的运行状况,提升客户服务感知.     

分布式智能开放运营架构及关键技术

随着电信运营商3G网络的部署、网络带宽的提速以及互联网应用高速发展的冲击,电信运营商面临前所未有的压力。运营商需要发挥网络和客户优势,转向对业务、平台、客户、界面等商业资源运营,并且整合网络与客户资源,创造新的商业模式。文章首先给出了电信行业面临的新威胁与挑战,分析电信运营商转型的优势、运营和商业模式转型的方法,提出分布式智能开放系统(DIOS),重点讨论了系统架构和关键技术。     

基于Seam的企业客户服务平台设计与实现

为了提高企业对客户信息化服务水平和整体运作效率,减轻工作人员的劳动强度,提升服务品质,全面降低企业运作成本,设计了一种基于Web的客户服务平台。重点研究了Seam的系统模型以及其总体架构、业务流程、功能模块和物理结构。应用结果表明,该方案可有效地集成和管理实现企业客户服务信息管理系统的网络化,系统实施之后,企业客户服务的工作效率得到了明显的提高。     

A case study of strategic engineering decision making usingjudgmental modeling and psychological profiling

This paper focuses on the role that judgmental modeling played in helping a large international engineering company plan its future production environment and also on how psychological profiling can help us to understand how different individuals within the decision-making team contribute to the overall decision. In this case study, two strategic decisions had to be made: which production process to use and which projects to allocate to the identified process. The decisions were complicated by the fact that different members of the management team were responsible for different elements of the decision. There was extensive interchange and negotiation between these various parties throughout the decision-making process, and for both decisions the use of judgmental modeling was found to have advantages in terms of structuring the decision process and in rank-ordering the potential outcomes. A comparison is made of the rank orders of the different potential outcomes before and after the use of judgmental modeling, and the psychological profiles of the individuals are used to provide further insights into how decision makers change their points of view over the life of the decision     

Modeling Spatial and Temporal Dependencies of User Mobility in Wireless Mobile Networks

Realistic mobility models are fundamental to evaluate the performance of protocols in mobile ad hoc networks. Unfortunately, there are no mobility models that capture the non-homogeneous behaviors in both space and time commonly found in reality, while at the same time being easy to use and analyze. Motivated by this, we propose a time-variant community mobility model, referred to as the TVC model, which realistically captures spatial and temporal correlations. We devise the communities that lead to skewed location visiting preferences, and time periods that allow us to model time dependent behaviors and periodic reappearances of nodes at specific locations. To demonstrate the power and flexibility of the TVC model, we use it to generate synthetic traces that match the characteristics of a number of qualitatively different mobility traces, including wireless LAN traces, vehicular mobility traces, and human encounter traces. More importantly, we show that, despite the high level of realism achieved, our TVC model is still theoretically tractable. To establish this, we derive a number of important quantities related to protocol performance, such as the average node degree, the hitting time, and the meeting time, and provide examples of how to utilize this theory to guide design decisions in routing protocols.     

电力企业客户细分模型研究

通过客户细分,可以帮助电网公司更为准确地掌握用电客户差异化服务的业务需求,协助提供符合实际需要的主动服务,最终取得提升客户用电体验满意度和降低电网公司服务成本的成效。从电网公司用电客户细分现状与应用需求出发,结合广东电网客户细分的各类应用场景,提出了基于客户价值区间的客户细分、K-Means聚类客户细分与基于决策树的客户细分三种细分模型,研究并创新性构建了细分模型从目标群体选择、细分模型层级管理到细分结果的深度分析总结三步客户细分机制,为电网公司个性化优质服务策略的制定奠定了基础。     

AT&T's MPLS OAM architecture, experience, and evolution

This article provides an overview of AT&T's MPLS OAM architecture, and gives examples of operational experience. Hallmarks of the architecture are a single, converged, and integrated MPLS/optical network, and the evolution to fully automated, zero-touch network operation. The concept of one converged IP/MPLS architecture will reduce operations, development, and capital costs. The concept of zero aims to bring full automation for every human-to-computer interaction currently required for setting up and maintaining network services, delivering services to customers in real time with zero defects and cycle time, and supporting both a network as well as an operational environment with six nines reliability. This approach effectively opens the network to the customer, enabling new levels of customer network management, service creation, and ordering, and empowering enterprise customers with the tools to create their own network services as they transform their own internal networks. In the article we describe AT&T's MPLS-enabled services, the corresponding MPLS operations architecture (including MPLS MIBs), our MPLS OAM operational experience, and MPLS OAM evolution needs for MPLS MIB enhancements and new network capabilities. By applying technologies such as artificial intelligence, self-healing/self-identifying network elements, expert systems, rules-based processes, and automatic speech recognition, the architecture will migrate from a predictive network that monitors, correlates, and recommends action; to an adaptive network that monitors, correlates, and takes action; to a cybernated network that has integrated components that dynamically manage by business rules and policies. We give several examples of how AT&T is already investing in and implementing this future vision, and conclude by challenging network researchers, developers, and key industry players to apply new technologies in fully realizing the operational vision.