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The Changing Landscape of Operational Support Systems (OSS): Technologies, Solutions, and Organizational Impacts

The Changing Landscape of Operational Support Systems (OSS): Technologies, Solutions, and Organizational Impacts

Operational Support Systems (OSS) are the essential set of tools required for a Communications Service Provider (CSP) to design, deploy, monitor and maintain the content, networks and services that their customers pay to use. There are significant changes underway in the CSP industry that are causing fundamental re-evaluations of business models, technology stacks and service offerings. These disruptions to the status quo are similarly influencing, and being influenced by, OSS.

This research assesses a range of relatively nascent technologies that have the potential to change the dynamic of OSS, whether via the networks they manage, or as building blocks on which to build better OSS tools. The report evaluates various technologies including cloud delivery, network virtualization, network security, Big Data, Machine Learning and Predictive Analytics, resource models, orchestration and automation, wireless sensor networks, IoT/ M2M, Self-organizing Networks (SON), software development models, and standards such as ITSM / ITIL.

This report is must-reading for anyone involved in planning or optimizing OSS as well as anyone with a vested interest in realizing positive financial returns from OSS investment. All purchasers of this report will be entitled to Self-Organizing Networks (SON) Challenges and Market Opportunities for 3G, LTE, and Beyond, Fourth Edition at no additional cost. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:

SDN solution providers
Network and services integrators
Cloud and virtualization companies
Fixed and mobile network operators
OSS/BSS products and services suppliers
Next generation network infrastructure providers
Third party providers of content, commerce, and apps

Companies in Report:

ABB
Accenture PLC
Acme Packet
Aeris
Akamai
Alcatel Lucent S.A.
Amazon
Amdocs Inc.
Apache
Apple
AT&T
Big Machines
Black Ridge
BlueKai
BMC
Bosch
Brocade
BT Group
CA Technologies
Canonical
CENX
Certes
Ciena
Cisco
Clarity (part of Synchronoss)
Cloudera
CloudFoundry
Collective Intellect
Comptel
ConceptWave
Covisint Corporation
DataStax
Digi-Data (part of Synchronoss)
Docker
Embrane
EMC
Ericsson (Telefonaktiebolaget L. M. Ericsson)
European Telecommunications Standards Institute (ETSI)
Fabrix
Facebook
Fastwire
F-Secure (part of Synchronoss)
GE
GenBand
GEOSS
Google
Guavus
Hewlett Packard Company
Hortonworks
Huawei
IBM Corporation
InfoVista
Intel
Intucell
Juniper Networks
Lightbridge Communications Corporation
Linux Foundation
LiveLOOK
Metacloud
MetraTech
Metro Ethernet Forum (MEF)
Microsoft
Mirror 42
Miyowa (part of Synchronoss)
Moogsoft
Neebula Systems
NetCracker Technology Corp. (part of NEC)
Nokia Networks
NTT Communications Corporation
Nuel (part of Huawei)
Open Networking Foundation (ONF)
OpNet
Optimi
Oracle Corporation
Pivotal
Riverbed
Samsung
SAS
Satyam
Sentilla
ServiceNow
SevOne
Siebel (part of Oracle)
Silver Peak
Spirent
Splunk
Strumsoft (part of Synchronoss)
Subex
Sunrise Technologies
Synchronoss Technologies
Tail-f
Tata Consultancy Services Limited
Tech Mahindra Limited
Telcocell
Telcordia (part of Ericsson)
TeleOSS
ThingWorx (part of PTC)
TimelessMIND
TM Forum
TOA Technologies
Truviso
UBIqube
Verizon
Voxmobili (part of Synchronoss)
WANDL
WindRiver (part of Intel)
Wisor (part of Synchronoss)
Younited (part of Synchronoss)
Zenoss



General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.


1 Executive Summary
1.1 Introduction
1.2 Topics Covered
1.3 Target Audience
1.4 Companies Mentioned
2 Introduction / Background
3 OSS Industry Overview
3.1 The Current Situation
3.2 Agents of Change
4 Technologies Impacting / Impacted by OSS
4.1 Cloud Delivery Models and Cloud Management
4.1.1 The ATL/BTL (Above-the-line / Below-the-line) OSS Model
4.1.2 Software as a Service (SaaS)
4.1.3 Platform as a Service (PaaS)
4.1.4 Infrastructure as a Service (IaaS)
4.1.5 Container Technology
4.2 Network Virtualisation
4.2.1 Network Functions Virtualization (NFV)
4.2.2 Software Defined Networking (SDN)
4.2.3 Lifecycle Service Orchestration (LSO)
4.2.4 Data Centre Infrastructure Management (DCIM)
4.2.5 Policy / Intent-based OSS
4.3 Network Security
4.3.1 Where the Money Flows Security Follows
4.3.2 Determining Value
4.4 Big Data
4.4.1 Stream Processing
4.4.2 Fresh or Frozen Data
4.5 Machine Learning and Predictive Analytic Techniques
4.5.1 Pre-cognitive Analytics
4.5.2 Network Operator Decision Support Systems
4.6 Commoditization of Hardware and Resources
4.7 Resource Aggregation
4.7.1 Open-source Collaboration and Ecosystems
4.7.2 Swarm Engineering
4.8 Automation and Orchestration
4.9 Wireless Sensor Networks and Mobility
4.9.1 Social Media
4.9.2 Mobility
4.9.3 Sensors
4.9.4 Data Overload is an OSS Opportunity
4.10 Self-Organising Networks (SON)
4.11 Software development lifecycles (SDLC)
4.11.1 DevOps
4.11.2 Agile Software Development
4.12 ITSM / ITIL
5 Vendors and Solutions
5.1 Accenture PLC
5.2 Alcatel Lucent S.A.
5.3 Amdocs Inc.
5.4 CENX
5.5 Ciena
5.6 Cisco
5.7 Comptel
5.8 GE
5.9 Guavus
5.10 Hewlett Packard Company
5.11 Huawei
5.12 IBM Corporation
5.13 Intel
5.14 Juniper Networks
5.15 Moogsoft
5.16 NetCracker Technology Corp. (NEC)
5.17 Nokia Networks
5.18 Oracle Corporation
5.19 ServiceNow
5.20 Splunk
5.21 Synchronoss Technologies
5.22 Tata Consultancy Services Limited
5.23 Tech Mahindra Limited
5.24 Ericsson (Telefonaktiebolaget L. M. Ericsson)
5.25 UBIqube
6 Summary and Anticipated Future Trends
6.1 Immunity from the Disruption of Virtualisation
6.2 Disruption Areas

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