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Showing posts with label Features. Show all posts
Showing posts with label Features. Show all posts

Wednesday, March 20, 2019

Inter team - Pushing for your bug fixes

When you work in a slightly larger software development organization, you will find that there are numerous cases where teams have dependencies on external teams for getting defect fixes. A simple example can explain. Say, there are multiple teams that need a function for coding / decoding music - and there are so many different audio formats, some of which have free solutions, and others which are paid solutions (and even in the paid solutions, there will be some that are very cheap and others, for some specific audio formats, which are very expensive). To further complicate this, each external solution will have its own set of legal formalities and requirements which may or may not be easy fort the organization to follow (some of the open source solutions are almost non-touchable for typical software organizations because they have some stringent requirements on their own, like insisting that any software that uses them must be open source in its own way).
And there can be numerous examples such as this; we used to have a simple XML parser that almost every software would need, and as a result, there was one team that was mandated to write such a parser and own the solution. Net net, where there are multiple teams that need a common functionality, it makes sense for a central team to create and own this common functionality, to update it as and when needed and provide the required updates to all the teams that depend on them.
However, this dependency on a central team can be tricky. With every organization and every team working on the concept of limited resources, the question of priority comes in. Teams that are more important and critical to the organization realistically have more say in the release timeline of central components, and more importantly, the bug fixes that go into the central component.
For a team that ranks somewhat lower on the priority, it can be a strugle to get the component with your desired bug fixes as per your schedule, and realistically no amount of hollering or screaming is going to change that basic truth. However, you still do need those bug fixes, so what do you do ? It is not a simple solution to write your own code to replace the component - it may not be allowed, the resources or other costs may not be available to do this, or your team may not even have the capability to do this. Another solution is to align your schedule with some of the more higher priority teams, atleast you would get a rock solid component with some of the high priority bug fixes in it. If this is not really a solution, then another method is to ensure your communication is top notch. The relevant people in your team (both management and technical) are part of any mailing lists or discussion groups that talk about the component, its features and defects. Similarly, there is a need to setup regular checkin meetings with the component team to ensure that your relevant defects are passed on along with the required priority and severity. Further, you need to communicate regularly with the other team to ensure that your defects remain on their radar (including with the product management function who decide on features and defect fixes). All of these measures help to ensure that your required defects or features get highlighted; whether they make it or not is still not guaranteed though. It does help though if you are able to get customer inputs about the defects or features which tries to increase the importance of the defect or feature.



Monday, October 7, 2013

What is Wifi technology? How does it work?

- Wifi has emerged as a very popular technology. 
- This technology has enabled the electronic devices to exchange information between them and to share the internet connection without using any cables or wires. 
- It is a wireless technology. 
- This technology works with the help of the radio waves. 
- The Wifi is defined as a WLAN (wireless local area network) product by the wifi alliance that is based on the standards defined by IEEE (802.11 standards). 
Most of the WLANs are based upon these standards only and so this technology has been named as wifi which is the synonymous with the term WLAN. 
- The wifi-certified trademark might be used by only those wifi products which have the complete certification for the wifi alliance inter-operability. 
- A number of devices now use wifi such as the PCs, smart phones, video game consoles, digital cameras, digital audio players, tablet computers and so on. 
- All these devices can connect to the network and access internet by means of a wireless network access point. 
- Such an access point is more commonly known as a ‘hotspot’. 
- The range of an access point is up to 20 m. 
- But it has a much greater range outside.  
- An access point can be installed in a single room or in an area of many square miles. 
- This can be achieved by using a number of overlapping access points. 
However, the security of the wifi is less compared to the wired connections for example Internet.
- This is so because a physical connection is not required by an intruder. 
- The web pages using SSL have security but the intruders can easily access the non-encrypted files on the internet. 
- It is because of this, that the various encryption technologies have been adopted by the wifi. 
- The earlier WEP encryption was weak and so was easy to break.
- Later, came the higher quality protocols such as the WPA2 and WPA. 
- The WPS or the wifi protected set up was an optional feature that was added in the year of 2007. 
- This option a very serious flaw which is that it allowed the recovery of the password of the router by an attacker.
- The certification and the test plan has been updated by the wifi alliance for ensuring that there is resistance against attacks in all the devices that have been newly certified.
- For connecting to a wifi LAN, a wireless network interface controller has to be incorporated in to the computer system.
- This combination of the interface controller and the computer is often called as the station. 
- The same radio frequency communication channel is shared by all the stations.
- Also, all the stations receive any transmission on this channel. 
- Also, the user is not informed of the fact that the data was delivered to the recipient and so is termed as the ‘best–effort delivery mechanism’. 
- For transmitting the data packets, a carrier wave is used. 
- These data packets are commonly known as the ‘Ethernet frames’. 
Each station regularly tunes in to the radio frequency channel for picking up the transmissions that are available. 
- A device that is wifi enabled can connect to the network if it lies in the range of the wireless network. 
- One condition is that the network should have been configured for permitting such a connection. 
- For providing coverage in a large area multiple hotspots are required. 
- For example, wireless mesh networks in London. 
- Through wifi, services can be provided in independent businesses, private homes, public spaces, high street chains and so on. 
- These hotspots have been set up either commercially or free of charge. 
- Free hotspots are provided at hotels, restaurants and airports. 


Tuesday, September 3, 2013

What is meant by load shedding?

The network is monitored by the network monitoring systems. These systems need to be robust and must be capable of inevitably coping with the situations in which the overload occurs. The network gets overloaded because of the nodes generating large volumes of data at high rates. Overload might also occur because of the burstiness of the traffic in its normal course of operation. For reducing the load of the network, load shedding techniques are applied. 

- Load shedding techniques have to be followed if the network is under a lot of stress. 
- This has to be done while monitoring the network for avoiding the packet loss that otherwise might be uncontrollable. 
- Load shedding involves sampling the incoming traffic. 
- CoMo or continuous monitoring has been developed to serve this purpose. 
- It uses such a load shedding scheme which can infer the query’s cost using the relation between the set of features of the traffic and the actual resource usage without having any knowledge of the plug-ins. 
- Here, traffic feature can be defined as a counter describing the incoming traffic’s particular property. 
The property might be any of the following:
Ø  Number of packets
Ø  Number of bytes
Ø  Flows
Ø  Unique IP destination address and so on.


- The CoMo consists of a prediction and the load shedding sub-system for intercepting the packets prior to sending them to the plug-in from the filter.
- A traffic query is implemented by this plug-in. 
- The system completes the process in 4 phases. 
- In the first phase, it forms a batch of packets for each 100ms of the traffic. - It then processes each of these batches for extracting a predefined traffic features’ set that is quite large. 
- From these, the most relevant sets are selected by the feature selection sub-system based up on the present stats of the CPU usage of the query. 
- The selected subset is then supplied as input for the “multiple linear regression subsystem”. 
- This is done for the prediction of the CPU cycles that the query requires for processing the whole batch. 
- If the prediction is greater than the capacity of the system, the batch is pre-processed by the load shedding subsystem for discarding the packet’s portion. 
The batch is discarded through packet or flow sampling. 

Load shedding is now being seen as an effective method for curbing the overload situations even in the real time systems. 
- It involves shedding excess of the load in such a way that the stability of the system is not disturbed and also the system buffers do not experience any overflows. 
- The idea for applying the technique of load shedding in the field of networking has been adopted from the concept of the electric power management.
- Here, the electric current is intentionally disconnected on particular lines when the demands for the power supply are higher than what is being supplied.
- CoMo is an open source system and can be quickly implemented and can be used for further deploying other network monitoring applications. 
- The system has been written using C language and uses a feature rich API. 
The system works by predicting the CPU usage of the system and thus anticipates about the resource requirements bursts that might occur in future. 
- The load shedding scheme used by the CoMo has the capability of automatically identifying the features using which the resource usage can be best modeled for each monitoring application.
This identification is made according to the previous resource usage measurements. 
- These measurements are then used for determining the system’s overall load and by what percentage the load must be shed. 


Friday, July 12, 2013

Sliding Window Protocols? – Part 1

- There are many types of data transmission protocols of which one type is the packet based data transmission protocols. 
- These protocols have a feature called the sliding window protocol.
- The sliding window protocols are a great help wherever the in-order delivery of the data packets demand reliability. 
- For example, the Data link layer of the TCP (transmission control protocol) model and OSI model demand such reliability and thus use window sliding protocol. 
- According to the concept of the sliding window protocols, a consecutive number which is unique is assigned to each and every portion of the transmission i.e., the packets.
- These numbers are used by the receiver for placing the packets it will receive in their correct order. 
- Also, with the help of these numbers, the missing packets can be identified and the duplicate packets can be removed. 
- One problem regarding the sliding window protocols is that it has kept no limits for the size of these numbers that are required. 

- An unlimited number of data packets can be allowed to be communicated at any instant of time if limits are placed on the number of packets involved in transmission or reception. 
- By this, we mean using the sequence numbers of fixed size. 
- By term window we refer to the transmission side. 
- It actually represents the logical boundary or limit of the number of packets that the receiver has to acknowledge. 
- The transmitter has to be informed by the receiver for each ACK (acknowledgement) packet regarding the maximum size or the window boundary of the current receiver buffer. 
- For reporting the window size of the received buffer, a 16 bit field is used in the TCP header. 
- The maximum limit or boundary of the window that we can have is 216 i.e., 64 KB. 
- When operating in the slow start mode, the counting of the transmitter begins with a low packet count.
- Gradually, the number of packets involved increases in every transmission after the ACK packet has been received. 
- Whenever it receives an ACK packet, the window slides logically by one packet for the transmission of a new packet. 
- On reaching the window threshold, one packet is sent by the transmitter for every one packet of ACK received. 
- Suppose the limit of the window is 10 packets and the transmitter is in slow start mode. 
- Then, first one packet will be transmitted followed by another two. 
- Between these two transmissions, it will send an ACK packet also. 
- This process will continue until the limit of 10 has reached. 
- After crossing the limit, the transmission is restricted to one i.e., for every ACK packet received only one data packet is transmitted. 
- When viewed during simulation, it seems as if the window is shifting by distance of one packet whenever an ACK packet is received. 
- For avoiding the traffic congestion, the sliding window protocol works up a great deal.
- In this way the application layer would not have to worry about transmission the next set of data packets. 
- It can continue to do so since the sliding windows of the packet buffer will be implemented on both the sides i.e., the receiver’s and the sender’s side by the TCP. 
-However, the network traffic influences the window size dynamically to a great extent. 
- In order to achieve the highest possible throughput, care should be taken for not forcing the transmitter to stop the transmission before one RTT or round trip delay time by the sliding window protocol. 
- The bandwidth delay product of the links in the communication should be less than the limit of the data amount that can be sent before sending ACK packet. - If this condition is not met, the links’ effective bandwidth will be limited by the protocol. 


Sunday, May 26, 2013

Where are artificial neural networks applied?


The artificial neural networks have been applied to a number of problems in diverse fields such as engineering, finance, medical, physics, medicine, and biology and so on. 
- All these applications are based on the fact that these neural networks can simulate the human brain capabilities. 
- They have found a potential use in classification and prediction problems. 
These networks can be classified under the non-linear data driven self adaptive approaches. 
They come handy as a powerful tool when the underlying data relationship is not known. 
- They find it easy to recognize and learn the patterns and can correlate between the input sets and the result values.
- Once the artificial neural networks have been trained, they can be used in the prediction of the outcomes of the data. 
- They can even work when the data is not clear i.e., when it is noisy and imprecise. 
- This is the reason why they prove to be an ideal tool for modeling the agricultural data which is often very complex. 
- Their adaptive nature is their most important feature.
- It is because of this feature that the models developed using ANN is quite appealing when the data is available but there is a lack of understanding of the problem.
- These networks are particularly useful in those areas where the statistical methods can be employed. 
- They have uses in various fields:

    1. Classification Problems:
a)   Identification of underwater sonar currents.
b)   Speech recognition
c)   Prediction of the secondary structure of proteins.
d)   Remote sensing
e)   Image classification
f)    Speech synthesis
g)   ECG/ EMG/ EEG classification
h)   Data mining
i)     Information retrieval
j)    Credit card application screening

  1. Time series applications:
a)   Prediction of stock market performance
b)   ARIMA time – series models
c)   Machine robot/ control manipulation
d)   Financial, engineering and scientific time series forecasting
e)   Inverse modeling of vocal tract

  1. Statistical Applications:
a)   Discriminant analysis
b)   Logistic regression
c)   Bayes analysis
d)   Multiple regression

  1. Optimization:
a)   Multiprocessor scheduling
b)   Task assignment
c)   VLSI routing

  1. Real world Applications:
a)   Credit scoring
b)   Precision direct mailing

  1. Business Applications:
a)   Real estate appraisal
b)   Credit scoring: It is used for determining the approval of a load as per the applicant’s information.
c)   Inputs
d)   Outputs

  1. Mining Applications
a)   Geo-chemical modeling using neural pattern recognition technology.

  1. Medical Applications:
a) Hospital patient stay length prediction system: the CRTS/ QURI system was developed using a neural network for predicting the number of days a patient has to stay in hospital. The major benefit of this system was that money was saved and better patient care. This system required the following 7 inputs:
Ø  Diagnosis
Ø  Complications and comorbidity
Ø  Body systems involved
Ø  Procedure codes and relationships
Ø  General health indicators
Ø  Patient demographics
Ø  Admission category

  1. Management Applications: Jury summoning prediction: a system was developed that could predict the number of jurors that were actually required. Two inputs were supplied: the type of case and judge number. The system is known to have saved around 70 million.
  2. Marketing Application: A neural network was developed for improving the direct mailing response rate. This network selected those individuals who were likely to respond to the 2nd mailing. 9 variables were given as the input. It saved around 35 % of the total mailing cost.
  3. Energy cost prediction: A neural network was developed that could predict the price of natural gas for the next month. It achieved an accuracy of 97%. 


Tuesday, May 14, 2013

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. 


Thursday, May 9, 2013

What is a thread? What is meant by multi-threading?


About Thread

- A thread is a smaller instance of a process i.e., a sequence of instructions and an operating system scheduler can manage it independently. 
- A thread is sometimes also called as the light weight process. 
- The way these threads and processes are implemented is different for different operating systems. 
- But in majority of the cases threads are contained within a process. 
- The same process can have more than one thread. 
- These threads have to share the resources including memory while different processes may not share these. 
- In simple words, we can say that the instructions or code and the context or the values of the process are shared by its constituting threads. 

In this article we focus on threads and multi-threading.

- Multi-threading is a task of multiprocessor systems.
- But even single processor systems can do it by time division multiplexing just like the multitasking. 
- In TDM context switch occurs between the many threads. 
- This happens many times and so it seems to the user that a number of processors are being executed concurrently.
- However, in multiprocessor systems concurrency can be truly achieved since every processor processes one thread and so many threads are executed simultaneously. 
- Both multiprocessor and time threading is supported by most of the modern operating systems with help from the process scheduler. 
- The threads can only be manipulated through a system and this all is facilitated by the kernel of the operating system. 
- This is why some implementations have been named as the kernel thread. 
- An example of kernel thread is the LWP or the lightweight process and it shares same state as well as info. 
- Some programs even use user space threads when threading with the help of signals and timers etc. 
- These programs perform a kind of ad hoc time slicing. 
- Some may take threads and processes to be the same but there is a considerable difference between the two:
  1. Processes are independent whereas the threads are a subset of the processes.
  2. More state information is contained in threads whereas the same process state, resources and memory are shared by all the threads contained in that process.
  3. Address spaces of different processes are different whereas the same address space is also shared by the threads.
  4. IPC or the inter–process communication is the only medium for the processes to communicate with each other.
  5. The threads within the same process are switched with context switch which is faster than that of the processes.

Features of Multi-threading

- Multi-threading is now among the widespread programming models. 
- The major characteristic feature of this model is that multiple threads can execute within the same process context. 
- Even though the resources of the process are shared by the threads, they execute independently. 
- The most widespread application of this model is in parallel computing.
- Full advantage of this technology can be taken only when it is applied to a multiprocessor system or a distributed system. 
- This is so because the program threads have a natural tendency to heed to the true concurrent execution. 
- But in these cases, necessary precautions must be taken for avoiding the race conditions and other undesirable behavior. 
- For the correct manipulation of data thread synchronization is also important. - Mutually exclusive operations are another requirement of the threads for preventing the simultaneous modification of the common data. 
- If these primitives are used carelessly, then it can lead the system to a deadlock. 
- Another feature of multi-threading is that it is always responsive to I/P. 
- This can be contrasted with the single threaded applications where if one block occurs, the whole program freezes.


Wednesday, April 17, 2013

What are Real-time operating systems?


- The RTOS or a real time operating system was developed with the intention of serving the application requests that occur in real time. 
- This type of operating system is capable of processing the data as and when it comes in to the system. 
- This it does without making any buffering delays. 
- The time requirements are processed in 10ths of seconds or even on much smaller scale. 
A key characteristic feature of the real operating system is that the amount of time they take for accepting and processing a given task remains consistent. 
- The variability is so less that it can be ignored totally.

Real time operating systems also there are two types as stated below:
  1. The soft real –time operating system: It produces more jitter.
  2. The hard real – time operating system: It produces less jitter when compared to the previous one.
- The real time operating systems are driven by the goal of giving guaranteed hard or soft performance rather than just producing a high throughput. 
- Another distinction between these two operating systems is that the soft real time operating system can generally meet deadline whereas the hard real time operating system meets a deadline deterministic ally.
- For the scheduling purpose, some advance algorithms are used by these operating systems. 
- Flexibility in scheduling has many advantages to offer such as the cso (computer system orchestration) of the process priorities becomes wider.
- But a typical real time OS dedicates itself to a small number of applications at a time. 
- There are 2 key factors in any real –time OS namely:
  1. Minimal interrupt latency and
  2. Minimal thread switching latency.
- Two types of design philosophies are followed in designing the real  time Oss:
  1. Time sharing design: As per this design, the tasks are switched based up on a clocked interrupt and events at regular intervals. This is also termed as the round robin scheduling.
  2. Event – driven design: As per this design, the switching occurs only when some other event demands higher priority. This is why it is also termed as priority scheduling or preemptive priority.
- In the former designs, the tasks are switched more frequently than what is strictly required but it proves to be good at providing a smooth multi – tasking experience. 
- This gives the user an illusion that he/ she is solely using the machine. 
- The earlier designs of CPU forced us to have several cycles for switching a task and while switching it could not perform any other task. 
- This was the reason why the early operating systems avoided unnecessary switching in order to save the CPU time. 
- Typically, in any design there are 3 states of a task:
  1. Running or executing on CPU
  2. Ready to be executed
  3. Waiting or blocked for some event
- Many of the tasks are kept in the second and third states because at a time the CPU can perform only one task. 
- The number of tasks waiting to be executed in the ready queue may vary depending on the running applications and the scheduler type being used by the CPU. 
- On multi – tasking systems that are non – preemptive, one task might have to give up its CPU time to let the other tasks to be executed. 
- This leads to a situation called the resource starvation i.e., the number of tasks to be executed is more and the resources are less.


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