Question:

Discuss about the Report for Telecommunication Management Network.

Answer:

Introduction:

The Telecom-Australia services division had a network management environment distributes across Victoria. Their aim was planning the acquisition to expand their customer base.

I have researched Telecommunication Management Network software providing service assurance solution. This intends to unify the fault, performance and topology and service level management in one scalable platform.

The following report includes the network management architecture, protocols in TMN architecture, fault management and fault detections. Moreover, the study also analyses the configuration state and software level of network resources, disaster recovery plan, QoS or Service-Level Agreement and parameters in fault management model.

1. Identification of various protocols in the TMN architecture model:

With a significant amount of the fielded equipment providing heterogeneous interfaces, I have pushed to encourage the development of a single set of protocols and service specifications to manage these networks. Requirements have been levied by the ITU to encourage the integration of TMN capable services into network equipment (Ding 2016). For example, new protocols must now include a General Description of Managed Objects (GDMO) based Management Information Base.

Figure 1: Network Management Architecture

(Source: Created by Author)

Explanation of the above diagram:

In the above description, the NetFlow Collector gets connected to the Flow Storage and Analysis Console. Here the entire traffic is analyzed, leveraging the technologies of flow. This delivers the real time visibility. This is done into the network bandwidth performance.  On the other hand, the collector is inter-connected to the Netflow Exporter. This increases the security visibilities. This is done by deploying on firewalls, dedicated capture hosts and servers. Further, this is linked to the Internet, various remote sites and the LAN.

The protocols are described below.

2. Analyzing the fault management process and fault identification:

2.1. The fault management process:

Fault management is a term used in network management, describing the overall processes and infrastructure associated with detecting, diagnosing, and fixing faults, and returning to normal operations.

The overall process of managing the complete lifecycle of a fault consists of the various steps. Firstly I consider the immediate discarding of data from obviously-failed sensors. The sensors are already known to be failed and still likely to be under repair or undergoing calibration. Next comes the filtering to reduce high-frequency noise, event generation, problem detection, problem diagnosis and predicting the impact of the detected and diagnosed problem (Ilieva-Obretenovaa 2016).

2.2. The fault identification process:

I can identify the faults by receiving events such as syslog and Simple Network Management Protocol (SNMP) traps from network devices, polling network device MIBs, and identifying real or potential error conditions and setting thresholds that trigger events. Also, the NMS should be able to provide event correlation as well as reporting and tracking (Martín-Montes, Burbano and León 2017). The NMS used should also offer a northbound interface for exporting critical messages to a higher level manager or MoM (manager of managers).

In an ideal environment, the fault manager would collect both syslog and SNMP information, then filter that information, and pass it to a MoM for further processing. This method helps decrease the amount of data that an end user needs to see or react upon (Martinez et al. 2014).

3. Configuration state and software level of network resources:

3.1. Configuration state:

The telecommunication Management Architecture is decomposed according to the five OSI functional areas, Fault, Configuration, Accounting, Performance and Security. Configuration Management is concerned with managing the configuration of resources in the Telecommunication architectures. As such, it is more specifically called Resource Configuration Management or RCM. I thought initially that the RCM should only manage the resources of the Network, Service and Computing architectures. There are scope and necessity for managing the resources of the management architecture itself.

Figure 2: “The Classification of Resources”

(Source: Ieeexplore.ieee.org, 2017)

Layering is an important concept in Telecommunication. The concepts of layering and decomposition of the overall architecture are orthogonal: each of the architectures can be split into Service, Resource and Element layers. The management architecture supports management services which should be seen as specializations of general telecommunications services; as such, they should conform to Telecommunication principles (Yamanaka et al. 2016).

3.2. The software level:

One of the main motivations for the Telecommunication initiative was the modernization of the network. The network operation is based on control plane functions with protocol-based interactions between software embedded in local switches and centralized service logic. The IN techniques have been successful for implementing enhanced telephony services, but it is more difficult to introduce modern, advanced services such as multi-media, multiparty communications mechanisms to support applications such as joint document editing (Sallabi and Shuaib 2016).

4. The disaster recovery plan:

Power loss, equipment failure, supplier faults and damaged phone lines can and do occur on a regular basis. Therefore, I think that a disaster recovery plan in place that covers our phone lines and business broadband is a no-brainer (Ramirez-Perez and Ramos 2016). I think that businesses should consider the benefits of having a proactive telecoms DR plan ready to react within minutes to unforeseen circumstances.

The staff may rely on their internet connection or telephone to do their job meaning that the business may suffer severe financial losses while workers are idle and waiting for the service to resume.

Here at Network Telecom, activities are done to ensure minimum business downtime and safeguard your business continuity. The proactive approach can prevent problems, making sure that the communications run smoothly at all times.

The Possible DR options:

5. Quality of service or Service Level Agreement management for supporting the various modes of accounting and alarm handing:

5.1. Quality of service:

I think that the QoS is specific to the service. Each service may be expressed by a set of parameters that are specific to it. Another characteristic is that QoS is an end-to-end issue. This means that all entities in the path between the parties are concerned to make the service possible and all the segments are involved in the process of QoS guarantee (Xing et al. 2016).

According to me, to provide and sustain QoS, resource management must be QoS-driven. I think that to allocate resources the resource management system must consider different parameters

5.2. The Service Level Agreement (SLA):

The SLA specifies the terms of the agreement and how much the customer will pay for those services. For example, an SLA between a telecom carrier and its customers may specify the following:

• The minimum bandwidth that will be provided.
• The amount of burst bandwidth that the customer can use the minimum and the charge that will be applied to that bandwidth.
• The amount of time the service provider guarantees the service will be up and running, usually a percentage such as 99.95 percent of the time (Ata and Tonouchi 2017).
• Penalties for not meeting service requirements. For example, an extra amount of free service in the next month, or nullification of the contract if the provider continues to fail to meet its requirements.
• As the service is packet-oriented over shared links, the level of QoS that will be provided for specific types of services. For example, the prioritization for real-time traffic such as voice could be considered (Bu et al. 2016).
• Equipment setup, on-site service assistance, and help desk support.

6. Identifying the monitoring parameters in the context of fault management:

Faulty network devices can pose a real threat to continuous network availability. The most likely causes include hardware issues, high CPU/memory utilization, high errors and discards, QoS issues and so on (Maupin 2016). Using network fault management tools help us to locate devices with suspicious activity.

7. Discussions on the data collection methodology:

7.1. Various data collection techniques:

With a clear definition of what to collect and who the user is, the question of how to collect data records becomes relevant. Common terms are meter and metering. The term meter describes a measuring process, even though a more precise definition is required for accounting purposes (Lin et al. 2015). The following details need to be considered for metering.

• Meter placement, at the device interface or the central processor
• Unidirectional or bidirectional collection
• Collection accuracy
• Granularity, which means aggregating packets into flows or aggregating multiple meters into a single value
• Collection algorithm, which means inspecting every packet with a full collection, or only some packets with sampling
• Inspecting the packet content for selection with filtering
• Adding details to the collected data sets, such as time stamps and checksums
• Export details, such as protocols, frequency, compression, and security

7.2. Explanation of techniques used to search relevant data over all mediums of information:

The meter describes a measuring process, even though a more precise definition is required for accounting purposes. In other words, it describes the measurement function in the network element or a dedicated measurement device (Bu et al. 2016). On the other hand, metering is the process of collecting and optionally preprocessing usage data records at devices in the network. These devices can be either network elements with integrated metering functionality or a dedicated measurement device or black box that is specifically designed as a meter.

7.3. Explanation of process implemented to analyze the data collected:

The two processes that could be implemented for analyzing the data collected are discussed below.

Passive monitoring:

It is also referred to as “collecting observed traffic,” this form of surveillance does not affect the user traffic because it listens to only the packets that pass the meter. Examples of passive monitoring functions are SNMP, RMON and Cisco NetFlow Services.

Active monitoring:

It introduces the concept of generating synthetic traffic, which is performed by a meter that consists of two instances (Lin et al. 2015). Here, both the instances can be implemented in the same device or at two different devices.

7.4. Demonstrating the evidence of the process implemented to analyze data:

A simple evidence of an active test is to set up a phone call to check if the destination’s phone bell is operational. The Cisco IP SLA feature is an instantiation of active measurement. The main argument for passive monitoring is the bias-free measurement, while active monitoring always influences the measurement results. On the other hand, active measurements are easily implemented, whereas some passive measurements, such as the ART MIB, increase the implementation complexity (Ramirez-Perez and Ramos 2016).

Unidirectional concepts, such as Cisco NetFlow, collect traffic in one direction only, resulting in multiple collection records. The major distinguisher between different passive monitoring techniques, in this case, is unidirectional versus the bidirectional type of collection.

7.5. Selection of key drivers that will result in the maximum impact on the topic of research:

Probabilistic Packet Sampling:

Probabilistic sampling describes a method in which the likelihood of an element’s selection is defined in advance.

Stratified Sampling:

For the sake of completeness, the theoretical aspects of stratified sampling are highlighted next. Stratified sampling takes the variations of the parent population into account and applies a grouping function before applying sampling (Bu et al. 2016).

Filtering at the Network Element:

Filtering is another method to reduce the number of collection records at the meter. Filters are deterministic operations performed on the packet content, such as match/mask to identify packets for collection.

7.6. Explanation of process implemented to keep research on track:

Conclusion:

The TMN originated as a strategic goal to create or identify standard interfaces that would allow a network to be managed consistently across all network element suppliers. The concept has fostered and tracked a series of interrelated efforts at developing standard ways to define and address network elements. I do think that an essential contribution of this study is how strategy is developed and sustained over different target market in the telecommunication sector. The future commitment of the customers to the organization depends on perceived marketing element. The report concludes that because the methods and techniques of the TMN have been demonstrated to be useful, and even essential to the design of complex management systems, I do not think that they should be replaced without careful consideration.

References:

Ata, S. and Tonouchi, T., 2017. Management of Information, Communications, and Networking: from the Past to the Future. IEICE Transactions on Communications, 100(9), pp.1614-1622.

Bu, X., Fu, G., Zhou, L. and Li, B., 2016, August. Research on power IMS communication network updating method. In Electronic Information and Communication Technology (ICEICT), IEEE International Conference on (pp. 53-56). IEEE.

Ding, J., 2016. Advances in network management. CRC press.

Freeman, R.L., 2015. Telecommunication system engineering(Vol. 82). John Wiley & Sons.

Ieeexplore.ieee.org. (2017). A statistical approach to IP-level classification of network traffic – IEEE Conference Publication. [online] Available at: http://ieeexplore.ieee.org/document/4024113/ [Accessed 7 Nov. 2017].

Ilieva-Obretenovaa, M., 2016. Information System Functions for SmartGrid Management. Sociology, 6(2), pp.96-103.

Lin, Y., Wang, Y.B., Zhang, H. and Yang, J.H., 2015, June. Research on Information Models and Modelling Methods of the New Generation of OSS for Data Management. In International Conference on Computer Information Systems and Industrial Applications. Atlantis Press.

Martinez, A., Yannuzzi, M., López, V., López, D., Ramírez, W., Serral-Gracià, R., Masip-Bruin, X., Maciejewski, M. and Altmann, J., 2014. Network management challenges and trends in multi-layer and multi-vendor settings for carrier-grade networks. IEEE Communications Surveys & Tutorials, 16(4), pp.2207-2230.

Martín-Montes, A., Burbano, M. and León, C., 2017, June. Efficient services in the industry 4.0 and intelligent management network. In Industrial Electronics (ISIE), 2017 IEEE 26th International Symposium on (pp. 1495-1500). IEEE.

Maupin, M.S., 2016. Fighting the network: MANET management in support of littoral operations (Doctoral dissertation, Monterey, California: Naval Postgraduate School).

Ramirez-Perez, C. and Ramos, V., 2016. SDN meets SDR in self-organizing networks: fitting the pieces of network management. IEEE Communications Magazine, 54(1), pp.48-57.

Sallabi, F. and Shuaib, K., 2016, July. Internet of things network management system architecture for smart healthcare. In Digital Information and Communication Technology and its Applications (DICTAP), 2016 Sixth International Conference on(pp. 165-170). IEEE.

Schneider, J.R., 2015. Resolving Tactical Network Management Interoperability by Using Ontology. JOHNS HOPKINS APL TECHNICAL DIGEST, 33(1), pp.68-80.

Xing, Z., Teng, L., Gao, Q., Wang, M. and Wang, Y., 2016, February. Research on deployment scheme of the power synchronization network management system. In Advances in Energy, Environment and Materials Science: Proceedings of the International Conference on Energy, Environment and Materials Science (EEMS 2015), Guanghzou, PR China, August 25-26, 2015 (p. 77). CRC Press.

Yamanaka, A., Nakajima, S., Tomono, M. and Tomouchi, T., 2016. Management System. Open Distributed Processing and Distributed Platforms, p.99.

Zaman, F., Hogan, G., Van Der Meer, S., Keeney, J., Robitzsch, S. and Muntean, G.M., 2015. A recommender system architecture for predictive telecom network management. IEEE Communications Magazine, 53(1), pp.286-293.