What are the goals and properties of a routing algorithm?

Routing requires the use of routing algorithms for the construction of the routing tables.

A number of routing algorithms are today available with us such as:

1.   Distance vector algorithm (bellman ford algorithm)

2.   Link state algorithm

3.   Optimized link state routing algorithm (OLSR)

- In a number of web applications, there are a number of nodes which require communicating with each other via communication channels. 

- Few examples of such applications are telecommunication networks (such as POTS/ PSTN, internet, mobile phone networks, and local area networks), distributed applications, multiprocessor computers etc. 

- All nodes cannot be connected to each other since doing so will require many high powered transceivers, wires and cables. 

- Therefore, the implementation is such that the transmissions of nodes are forwarded by the other nodes till the data or info reaches its correct destination. 

- Thus, routing is the process of determining where the packets have to be forwarded and doing so.

Properties of Routing Algorithm
- The packets must reach their destination if there are no factors preventing this such as congestion.

- The transmission of data should be quick.

- There should be high efficiency in the data transfer.

- All the computations involved must not be long. They should be as easy and quick as possible.

- The routing algorithm must be capable of adapting to the two factors i.e., changing load and changes in topology (this includes the channels that are new and the deleted ones.)

- All the different users must be treated fairly by the routing algorithm.

The second and the third properties can be achieved using fastest or the shortest route algorithms. 

- Graphical representation of the network is a crucial part of the routing process.

- Each network node is represented by a vertex in the graph whereas an edge represents a connection or a link between the two nodes. 

- The cost of each link is represented as the weight of the edge in the graph. 

- There are 3 typical weight functions as mentioned below:

1.   Minimum hops: The weight of all the edges in the graph is same.

2.  Shortest path: The weight of all the edges is a constant non – negative value.

3.   Minimum delay: The weight of every edge depends up on the traffic on its link and is a non – negative value.

However in real networks, the weights are always positive.

Goals of Routing Algorithms

- The goal of these routing algorithms is to find the shortest path based up on some specified relationships that if used will result in the maximum routing efficiency. 

- Another point is to use as minimum information as possible.

- Goal of the routing algorithm is also to keep the routing tables update with all alternative paths so that if one fails, the other one can be used.

- The channel or the path that fails is removed from the table. 

- The routing algorithms need to be stable in order to provide meaningful results but at the same time is quite difficult to detect the stable state of an algorithm. 

- Choosing a routing algorithm is like choosing different horses for different courses. 

- The frequency of the changes in the network is one thing to be considered. 

- Other things to be considered include the cost function that is needed to be minimized and the calculation of the routing tables in a centralized fashion.

- For static networks the routing tables are fixed and therefore they require only simple routing algorithms for calculation. 

- On the other hand, the networks that are dynamic nature require distributed routing algorithms which are of course complex.

What is a Distributed System?

In the field of computer science, the distributed computing constitutes of distributed systems. 

- Multiple computers that are capable of communicating via a computer network together compose a distributed system. 

- All the computers in a distributed system work together in order to accomplish a common task.

- A common program is also required for running this whole system and is known as the distributed system. 

- Such programs for distributed systems are written using the process called the distributed programming. 

- Distributed computing involves the use of distributed systems for solving the computational problems.

- A distributed system divides the problem into much smaller tasks that are then given to one or more computers of the distributed systems. 

- These systems use message passing for communicating with each other. 

- The term distributed system earlier referred to the networks which had their hosts distributed over a geographical area. 

- This term was eventually refined and now is applied to a much broader concept. 

- It now also refers to the various autonomous processes that execute on the same system but maintain an interaction with other systems also through message passing. 

Because of the wide sense to which the concept is applied, it has no formal definition; rather the following properties are used for defining it:

1. There are many computational entities of the distributed system that are autonomous in nature and each of them possesses individual local memory. These entities are commonly referred to as the nodes.
2. By means of message passing these entities communicate with each other.

- A distributed system works towards a common goal which may involve solving a big computing problem. 

- On the other side, each node in a distributed system may have its own requirements. 

- The distributed system must provide communication means to the user and help in coordinating the use of the common resources.

Properties of Distributed Systems

Distributed systems possess many other typical properties as mentioned below:

1. It has the capability to tolerate the failures of the individual nodes or the computers.
2. The system’s structure cannot be determined in advance. It includes a number of factors such as number of computers, network topology, and network latency and so on. The computers in the system might be of many different types and so the links also. As a result the structure of a distributed system may alter while executing a distributed program.
3. The complete view of the distributed system is hidden from its nodes. They are provided only with a limited view or information about the system. Only a part of the input is known by each of the nodes.

- There are two terms which consistently overlap with the distributed computing namely parallel computing and concurrent computing. 

- The distinctions between these three are not clear at all. 

- At the same time a system may be called both a parallel one and a distributed one.

- Another thing about distributed systems is that the processors involved run in concurrence with each other but in parallel.

- Distributed computing in a more tightly coupled form is called parallel computing. 

- Thus, a loosely coupled form of parallel computing is the distributed computing. 

Two main reasons have been observed for using distributed computing:

1. Depending on the nature of the application it may require using a network connecting many other systems. For example, data produced by one system is required by others.
2. There are cases, where by theory and principle use of a single computer is possible but for the same case if a distributed system is used in practical then it might be more beneficial. For example, using a cluster of low – end computers for attaining the desired level of performance might be more cost efficient. 

What are principles of autonomic networking?

The complexity, dynamism, heterogeneity and so on are on ever rise. All these factors are making the infrastructure of our network insecure, brittle and un – manageable. Today’s world is so dependent on networking that its security and management cannot be risked. In terms of networking, we call this the ‘autonomic networking’. 

The goal of building such systems is to realize such network systems that have capability of managing themselves as per the high level guidance provided by the humans. But meeting this goal calls for a number of scientific advances and newer technologies.

Principles of Autonomic Networking

A number of principles, paradigms and application designs need to be considered.

Compartmentalization: This is a structure having extensive flexibility. The makers of autonomic systems prefer this instead of a layering approach. This is the first target of the autonomic networking.

Function re–composition: An architectural design has been envisioned that would provide highly dynamic, autonomic and flexible formation of the networks on a large – scale. In such architecture, the functionality would be composed in a fashion that is autonomic.

Atomization: The functionality are broken down in to smaller atomic units. Maximum re - composition freedom is made possible by these atomic units.

Closed control loop: This is one of the fundamental concepts of the control theory. It is now also counted among the fundamental principles of the autonomic networking. This loop is known for controlling and maintaining the properties of the controlled system as per the desired bounds. The target parameters are constantly monitored within the desired bounds.

The human autonomic nervous system is what that inspires the autonomic computing paradigm. An autonomic computing paradigm must then have a mechanism by virtue of which it can change its behavior according to the change in various essential variables in the environment and bring it back itself in to the state of equilibrium. 

Survivability can be viewed in the terms of following in case of autonomic networking:

1. Ability to protect itself
2. Ability to recover from the faults
3. Ability to reconfigure itself as per the environment changes.
4. Ability to carry out its operation at an optimal limit.

The following two factors affect the equilibrium state of an autonomic network:

1. The internal environment: This includes factors such as CPU utilization, excessive memory and so on.
2. The external environment: This includes factors such as safety against external attacks etc.

There are 2 major requirements of an autonomic system:

1. Sensor channels: These sensors are required for sensing the changes.
2. Motor channels: These channels would help the system in reacting and overcoming the effects of the changes.

The changes that are sensed by the sensor are analyzed for determining the viability limits of the variables. If the variables are detected out of this limit, then the system plans what changes it should introduce in to the system to bring them in their limit, thus bringing back the system in to its equilibrium state. 

What are characteristics of autonomic system?

Autonomic systems bring both challenges as well as opportunities for the future networking. The increasing numbers of users have had a negative impact on the complexity of the networks; it has also increased by multiple folds. Autonomic systems provide a solution for this problem. 

Characteristics of Autonomic System

1. High intelligence: These systems have more intelligence incorporated in to them which lets them tackle this increasing complexity easily.
2. Business Goal: They are driven by the business goal that the quality of experience of the user must be high. Even with the changing environment, there goals remain the same. But there are changes that take place in the low – level configurations. For example, when a user switches over to a low bandwidth network, the bit rate of the video has to be reduced in order to satisfy the goals of the business.
3. Complex operations: All the operations carried out in an autonomic system are complex in nature even for the simplest of the services. For example, authentication, video encoding, billing, routing, shaping, QoS prioritizing, admission control.
4. High level objectives: The human operator just has to specify the high – level objectives and it is left to the system whether it chooses to optimize one or more of the goals. In order to achieve this, the system has to translate these objectives in to low – level configurations.
5. Adaptability: The system has the ability to adapt itself to the current environment.
6. Policy continuum: There are a number of perspectives to this as mentioned below:

Ø  Business view: Includes guidelines, processes and goals.

Ø  System view: The service should be independent of the technology as well as the device that is being used.

Ø  Network view: It should be specific to technology but independent of the device.

Ø  Device view: Both technology and device specific.

Ø  Instance view: Operation should be specific to an instance.

7. Elements: The elements of the network are assumed to be heterogeneous by the autonomic communication systems whereas in plain autonomic computing the elements are taken to be as the homogeneous.
8. Distributed: These systems work up on a distributed environment.
9. Complexity: The complexity in autonomic systems is more because of the complex autonomic loop that includes the following operations:

Ø  Interaction between the context  and the business goals

Ø  The MAPE (monitor, analyze, plan and execute) loop.

10. Reliability: In autonomic systems, the network has the authority to decide for itself focusing on high level objectives. Autonomic systems rely heavily up on artificial intelligence. However, there are issues associated with artificial intelligence like it becomes difficult to intervene in between when the things go wrong.It is quite difficult to know whether the system is doing the things it is supposed to do or not.

11. Scalability: This is another major characteristic of autonomic systems. It is required to keep track of the large amounts of knowledge and information. Autonomic systems have three tools to take care of this:

Ø Distributed ontologies

Ø Distributed large – scale reasoning

Ø Exchanging only the useful information

ØDistributing information among the different components of the autonomic network.

But in these cases, detection of the conflicts is a difficult task. For handling the various interactions taking place the various autonomic components efficient protocols are required. 

Currently two approaches have been suggested for developing the autonomic networking systems namely:

1. Evolutionary Approach: Incorporating the autonomic behavior in to the pre – existing infrastructure. This approach will consist of updates in increments till a fully autonomic system is developed. This approach is more likely to be adopted even though it requires a lot of patchwork.

2.  Clean slate approach: This approach is focused up on re – designing of the internet.

What is an Agile Process Improvement?

A process improvement program is successful only when the meaning of the word ‘process’ is clearly understood. Process means work. So when one improves, the other one also improves. The quality of the software depends a lot on the process. Whenever a change is introduced, a temporary drop in performance is always recorded. In most cases what happens is that the organization stops the implementation of changes fearing the disruption in the normal work since so much effort is required. To avoid such situations, the changes need to be adaptive. It is the agile process improvement that makes this possible. You might say that such a way of iterative improvement is not new. Well, the agile techniques introduce discipline in the whole program.

Stages of Agile Process Improvement

The following are the stages of the agile process improvement:

1. Initiating:

Ø  Stimulus of change

Ø  Set context

Ø  Build sponsorship

Ø  Charter infrastructure

2. Diagnosing:

Ø  Characterize current and desired states

Ø  Develop recommendation

3. Establishing:

Ø  Set priorities

Ø  Develop approach

Ø  Plan actions

4. Action:

Ø  Create solution

Ø  Test solution

Ø  Refine the solution

Ø  Implement solution

5. Learning:

Ø  Analyze

Ø  Validate

Ø  Propose future actions

- The improvement cycles are meant to be followed systematically so that the results might be obtained in time ranging from 2- 6 weeks.

- The whole process lets you maintain a balance the workload as well as the improvement. 

- The flow of the process is as follows:

1. Prioritized list of improvements
2. Detailed plan for the current cycle
3. Implemented improvement
4. Feedback

- After this process, the following becomes possible for the organization:

1. Identification and resolving of the issues earlier in the cycle.
2. Learning process regarding how to tackle difficulties and working of this process.
3. Adaption to the business needs that keep changing.
4. Giving response to the feedback.

- The sponsor holds the responsibility for prioritizing the improvement backlog at the start of each sprint. 

- Also, he is the one responsible for ROI. 

- Prioritization is a good tool for the sponsor to direct the change. 

- Using prioritization, the goals and feedback can be revised from quality assurance. 

- A focus can be kept on the benefit received from each improvement cycle. 

- PPQA deploys and evaluates the improvement in organization in every sprint. - The improvement package consists of 4 sprints namely:

1. Prototyping
2. Piloting
3. Deploying
4. Evaluating

- Active participation and leadership is required for a change to take place. 

- An endorsed vision and status quo is required for the beginning of the process. 

- Both of these are established via SCAMPI and CMMI. 

- The change is led by the management on an everyday basis.

- An excellent description is provided by the generic practices of CMMI for the leadership purpose.

- Similarly participation is a key element that is facilitated by the change team. - A vision is required for initiating the improvement project. 

- The initial improvement backlog is defined by 3 things namely scrumMaster, change team and the work owner i.e., the sponsor all based up on an assessment. 

- The organization is facilitated by the change team.

- With each sprint a tangible improvement is delivered. 

- The change is led by the management in a sprint.

- The effect introduced by the change is evaluated at the end of each sprint by PPQA. 

-The new improvements are defined by the work-owner who is also responsible for adding those in to the backlog of improvements and prioritizes it.

-Commitment is supported at the end of the sprint by appraisal.

-The improvements can also be continuously integrated in to the organization’s way of working. 

What is meant by Software Process Improvement?

About Software Process Improvement

- SPI or Software Process Improvement is a program that has been developed to provide guidance for the integrated long – range plan for the initiation and management of the SPI program. 

- SPI is based up on a model called the IDEAL model which has the following 5 major stages:

1. Initiating
2. Diagnosing
3. Establishing
4. Acting
5. Leveraging

- These 5 major steps form a continuous loop. 

- However, the time taken for the completion of one cycle varies from one organization to other. 

- Depending on the available resources an organization must be able to decide whether or not it would be able to commit to software process improvement. 

- SPI requires many activities to be carried out in parallel to each other. 

- Some part of the organization may take care of the activities in one phase while others take care of the other phase activities.

- Practically, the boundaries of the various stages in a software process improvement are not clearly defined. 

- The infrastructure also plays a great role in the success of the SPI. 

- The value added to SPI by infrastructure just cannot be underestimated. 

- It provides a great help in understanding its roles.

About Initiating Phase

- As the name indicates this is the starting point of the process. 

- This stage involves setting up of the improvement infrastructure. 

- Then the infrastructure’s roles and responsibilities are defined. 

- The resources are checked for availability and assigned.

- Finally, an SPI plan that will guide this initiating phase as well as the other higher stages. 

- It is during this stage that the goals of the software process improvement are defined and established based up on the organization’s business needs. 

- During the establishing phase these goals are further refined and specified.

- Two components are typically established namely:

Ø  A software engineering process group or SEPG

Ø  A management steering group or MSG 

About Diagnosing Phase

- In this stage, the organization as per the SPI plan starts. 

- This stage serves as foundation for the stages that will follow. 

- The plan is initiated keeping in view the vision of the organization along with its business strategy, past lessons, current business issues and long term goals. 

- Appraisal activities are carried out so that a baseline of the current state of the organization. 

- The results of these activities are reconciled with the existing efforts so as to be included in the main plan.

About Establishing Phase

 

- In this stage the issues to be addressed by the improvement activities are assigned priorities.

- Also, the strategies for obtaining a solution are also pursued. 

- The draft of the plan is completed as per the organization’s vision, plan, goals and issues. 

- From general goals, measurable goals are developed and put in to the final SPI plan. 

- Metrics essential to the process are also defined.

About Acting Phase

 

- Solutions addressing the improvement issues discovered in the previous stages are created and deployed in and out of the organization. 

- Other plans are developed for the evaluation of the improved processes.

About Leveraging Phase

 

- This stage is led by the objective of making the next pass through the process more effective. 

- By this time the organization has developed solutions and metrics concerning performance and achievement of the goals. 

- All this data obtained is stored in a process database that will later serve as source information for the next pass. 

- Also, this information would be used for the revaluation of the strategies and methods involved in the SPI program.

- Software process improvement activities work with two components namely, the tactical component and the strategic component. 

- The former is driven by the latter that is based up on the needs of the organization. 

What are Rational Unified Process building blocks?

Whenever we talk about iterative software development process frame works, the first name that comes to our minds is of the rational unified process. It is not just a single hard coded prescriptive process rather it is quite an adaptable and flexible process frame work. 

This frame work comes with several facilities, the best one being that your organization can tailor it according to their needs. 

What is Rational Unified Process?

- Unified process when specifically implemented is called as the rational unified process. 

- Rational unified process is counted among the best products of IBM and the credit for its development goes to the rational software division.

- The RUP comes with a hyper linked base consisting of the descriptions of several types of activities and a few sample artifacts. 

- A part of the IBM’s rational method composer (RMC) is occupied by the rational unified process.

- It allows the users to customize the process as per their needs. 

What are building blocks of Rational Unified Process?

In this article we are to talk about the building blocks of the rational unified process.

- These basic best practices of the rational unified process were developed as a result of the combination of the experience of many companies. 

- The building blocks are:

1. Iterative development with risk as its primary iteration driver.
2. Management of the requirements.
3. Employment of an architecture based up on components.
4. Visual modeling of the software.
5. Continuous verification of the quality.
6. Controlling the changes

- These best practices are used in the following two ways:

1. For driving the development process of the rational’s products.
2. To be used by the rational’s field teams so as to assist the customers in improving the predictability as well as the quality of the software development efforts.

- The task involves the assembling of the explicit process framework for the field of modern software engineering. 

- The delivery mechanism developed by the objector was based up on the HTML and employed in accomplishing this task.

- This task resulted in the creation of the rational unified process. 

- A set of content elements or the building blocks form the foundation for the rational unified process and give a description of the product that is to be produced and the required necessary skills. 

- They also give a detailed step by step explanation for achieving the specific development goals. 

Now we shall list all the building blocks of the rational unified process and discuss them in detail:

1. Roles: This building block can be defined as set consisting of related skills, responsibilities as well as competencies.
2. Work products: This building block gives the representation of thing that would result when a task would be completed inclusive of all the models and documentation produced during the course of the completion of that task.
3. Tasks: This building block gives a description of the units of works that are assigned to an element from the role which will produce a result that would be meaningful.

There are 9 disciplines in to which the tasks are categorized within each iteration. There are 6 engineering disciplines and 3 supporting disciplines which together make up total 9 disciplines. The 6 engineering disciplines are:

1. Business modeling
2. Requirements
3. Analysis and design
4. Implementation
5. Test and
6. Deployment

The following are the three supporting disciplines:

1. Configuration and change management
2. Environment and
3. Project management

The organization and the management of the above mentioned building blocks need to be solid and flexible in order to make the rational unified process a success which otherwise cannot be achieved.