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Distributed Systems

Distributed system refers to the network which mainly consist of the autonomous computers that are connected by the use of a distributed middleware. Besides this the distributed system also helps in the sharing of the various resources and the capabilities to the users with an integrated and a coherent network (Toprak-Deniz et al. 2014). This system consists of components which are concurrent helping in the sharing of the different resources like the software’s of a system which are connected to the networks. This report mainly discusses about the distributed systems, mobile distributed systems and non-distributed systems besides this the report also discusses about the theoretical concepts of the communication involved in the distributed systems. Comparing of the fault tolerance requirements in distributed systems and mobiles distributed system is also done in this report which also includes the social problems that are arising from the use of the ubiquitous distributed systems. The components of a distributed system can be multiple but generally they are autonomous in nature. The fault tolerance is generally greater in the distributed model than any other network mode (Rajguru and Apte 2012). There is also no need of a global clock in a distributed system as they can spread across different geographies. One more advantage of distributed system is that the price/performance of this system is much better.  

Distributed System mainly refers to a software system which is used for communicating the components located on the network computers so as coordinate the actions of the components by passing different messages. The main purpose of passing this message is to achieve a certain goal or a common goal (Garonne et al. 2014). The key goals of the distributed goal include the formation of an image of the single system without concealing of different types of details like the location, access, migration and many more, easy configuration and modification of the system, making the system much more secure than any single system and making less errors, boost of the performance and many more. Mobile distributed system is a form of distributed system which consist of some processes that runs on a mobile host. Communication networks helps in interconnecting the fixed and the mobile stations of a mobile distributed system. The fixed stations are located at a fixed location whereas the mobile stations are those which moves from one location to another within the network. Whereas the distributed system refers to the self-governing computers which appears to be a single computer to the users of the system. A memory or a clock is not shared between the several computers that are present in the system. Each computer has their own operating system and memory (Rao et al. 2013). They mainly communicate by exchange of messages over the communication network. 

Mobile Distributed System

Mobile distributed system is a form of distributed system which consist of some processes that runs on a mobile host. Communication networks helps in interconnecting the fixed and the mobile stations of a mobile distributed system. The fixed stations are located at a fixed location whereas the mobile stations are those which moves from one location to another within the network. Whereas the distributed system refers to the self-governing computers which appears to be a single computer to the users of the system. A memory or a clock is not shared between the several computers that are present in the system. Each computer has their own operating system and memory (Rao et al. 2013). They mainly communicate by exchange of messages over the communication network.

Ubiquitous distributed system is a form of distributed system which mainly includes the applications that are feasible to be different. These applications are embedded in the physical environment of the user and are integrated smoothly with the tasks that are performed on a daily basis. This is a new form of technology which aims at eliminating the time and the position barriers along with this technology is extremely inexpensive which are capable of providing availability to the users anytime and anywhere.

Distributed system

Non-distributed system

Mobile distributed system

The presentation tier and the middle tire are split in the physical as well as logical form so that they can run in different servers.

The presentation tier as well as the middle tier run on the same server.

The mobile host used in MDS or designed for cellular network connections.

Different types of clients can be supported by the use of the shared middle tier. The distribution of the application components across the different physical layers are permitted by this system (Ricci et al. 2012).

This consist of a simple architecture for the web applications along with this the development of different application is also faster in this system. Good OO design can be implemented along with well scaling which means handling of the much more requests. The cost is also less along with the availability of many open source stable web containers (Bobelin et al. 2012).

The mobile host communicates with the mobile support station. The mobile service station is used for providing service to the local mobile hosts.in a cell the MH in the MSS maintains the mobile network.

Because of its complexness it should be chosen when dictated according to the requirement. The performance is also affected. The applications involved in the system are hard to test as well as debug because of the dependency on the container services. Hampering of the OO design is also done in this system by using the central use of RMI. The handling of the expectations is also complex (Xu et al. 2014).

Only the web interface clients are supported by this system. The running of the whole system is done on a single server along with boosting up the performance. the components involved in the system cannot be freely allocated to the different physical layers. The transactions are managed by the use of codes. For the concurrent threading issues again there is a need of writing the codes (Kekatos et al. 2013).

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Inter-Process Communication mainly refers to the mechanism which is used by two or more processes to communicate with each other so as to exchange the data and to synchronize the activities (Ota et al. 2012). There are mainly two types of inter-process communication and this includes the:

Local inter-process communication makes it possible to allow one or more processes to communicate with each other in a single system and this are listed below:

  • Pipes: This helps in the passing the information from one process to the another. There exist two different type of pipes and they are “named pipes” and “unnamed pipes”. The unnamed pipes provide a one-way communication whereas the named pipes provide a two-way communication (Wang Zhu and Gomes 2012).
  • Signals: This is generally a software generated interrupt that is sent to the process whenever an event occurs.
  • Message Queuing: A message queue is used for the purpose of allowing the processes to exchange the data.
  • Semaphores: This is used for the purpose of synchronizing the activities of the processes concurrently so as to compete for the same resource in a system (Liu and Jiang 2013).
  • Shared memory: This helps in allowing the different memory segments to get shared among the process communication so as to make them capable of exchanging the data between them. This is mainly used for the purpose of fast communication between the different processes (Kumar and Garg 2013).
  • Sockets: This acts as the end point for the communications between the various processes. They mainly allow the communication taking place between a program of the client and the program of a server.

This helps in the communication of two or more processes with each other in some different systems. There are some networking protocols that are implemented in the remote inter-process communication (Verissimo and Rodrigues 2012).

Theoretical Concepts of Communication in Distributed Systems

The transport layer has the responsibility of end-to-end message transfer and this process of message transfer does not depend on the network that underlies this layer. And along with this it also controls the errors, fragmentation and flow control. This end-to-end transmission can be categorized into two types and this are mainly TCP or connection oriented and UDP or connectionless. The most sophisticated form is the TCP which provides a much reliable form of delivery (Agrawal and Zeng 2015). It is ensured by TCP that the computer which will be receiving the message is ready for it. A three-packet handshake is used in which both the sender as well as the receiver agrees with the fact that they are ready for communication. Second of all the TCP also makes it sure that the data is reaches to its right destination. A packet is automatically retransmitted whenever the packet is not acknowledged by the receiver. A TCP can split the larger packets into smaller packets whenever necessary and it is done so as to make the data travel reliably from the source to the destination (Agrawal and Zeng 2015). The packets are duplicated by the TCP and are rearranged whenever the packets arrive out of the sequence.

There are two major difference between TCP and UDP. First of all, UDP is connectionless. There does not exist any type of solid communication. Another difference between this two are that the packets received in case of UDP may not be arranged in the right order when the receiver will receive the package. This two difference proves UDP to be much faster as the extra overhead for checking of the errors in not present (Coulouris et al., 2011).

Failure can be classified into two categories and this are namely the hardware failure and software failure. Hardware failure involves the heat consumption and power consumption of the smaller circuits, the off-chip connections and the wirings and the quality of the manufacturing techniques. Problems may also be related with the connection or mechanical failures (Lee and Anderson 2012).

One of the important issue in the distributed system is the failure of the software’s. software bugs are mainly responsible for the downtime in the system. This residual bugs can be classified into two categories this includes the Heisenbug and Bohrbug. Heisenbug refers to that bug which seems to disappear or alter the changes whenever it is getting researched or observed. Bohrbug refers to those bugs that does not disappear or alter the changes when it is researched (Baldoni Bonomi and Raynal 2012).

Fault Tolerance in Distributed and Mobile Distributed Systems

There are other problems which are also associated with this system and this are listed below:

  • Halting failure: this happens whenever a component of the system simply stops. The only way of detecting this failure is by the use of timeout. When a computer freezes then it can be considered to be as a halting failure.
  • Fail-stop: this refers to the failure when some kind of notification is received by the other components of the system. One example of fail-stop is the telling of the network servers to the clients that it will go down.
  • Omission failure: This is the failure which occurs due to the lack of the buffering space resulting in the failure of the receiving and sending of the messages. The failure mainly occurs when the routers get overloaded.
  • Network failures: Breakage in the network link causes this type of errors.
  • Network partition failure: The main reason for this failure is whenever the message gets lost due to network failure in two sub-joint networks where a message can be sent. This sub-joint networks are formed due to fragmentation of the network.
  • Timing failures: This type of failure consist of the violation of the temporal property.
  • Byzantine failure: This is the failure which includes a number of faulty behavior like the data corruption or loss of data, malicious programs causing failures and many more.

Additional failures that are to be considered in case of “mobile distributed systems” are listed below:

  • Mobility: whenever a message is sent from the mobile support station to a non-local mobile host a search cost is incurred. The change of location of the mobile host makes the routing message get more complicated (Cheng et al. 2012). The completion time is increased whenever response is delayed to such a request unless and until mobile host reconnects with another mobile support station.
  • Consumption of the energy: Various components of the system consume a lot of energy and the components includes the CPU, display and many more along with this the transmission and reception of the messages also consumes a lot of energy.
  • Stable form of storage capacity: Most of the mobile distributed system has a limited memory capacity. Every process in the system requires a storage for the purpose of saving each snapshot of the different checkpoints (Chen and Ho 2015). There is also a lack of the stable storage device in the mobile host.
  • Bandwidth: Another issue that arises in the mobile distributed system is the lack or limited amount of communication bandwidth in the network.
  • Disconnections: This issue arises when one or more mobile host gets disconnected resulting in the prevention of the recording of the global state of an application which is executing on the mobile host.
  • Synchronization: Synchronization of the messages and the number of checkpoints by the process of checking the pointing algorithms is minimized because of the energy consumption and low bandwidth constraints.

Social issue is nothing but the matters which are directly or indirectly related to the effects on a person or a number of peoples in the society along with this this issues are also considered as the problems or controversies that are related to the moral values. The major social issues are listed below:

  • Civil right: This includes the access of the information’s by malicious users, exchange and many more.
  • Crime: this mainly includes the cybercrimes.
  • Disability rights: This issue includes the accessibility to the web, ubi-assistance and many more.
  • Social exclusion: This includes the computing for all the users and many more.

Social issues prove itself to be one of the most important aspect in building the model of security, privacy and trust in a ubiquitous system. People’s perception of technology can be greatly affected by the general social pressure of belonging to a group, knowing of all the thoughts of the other peoples, talking with other peoples who are affected by the system.

Some of the applications that are used for the purpose of reducing the social issues are listed below:

  • Use of real time detection
  • Use of RFID based authentication Protocol
  • Use of trust based security solutions
  • Avoidance of the information leakage
  • Verifications of the secret locally so as to prohibit man-in-middle attacks in the Ubiquitous distributed system
  • Use of biometrics for the purpose of identifying individuals.

Conclusion

The report helps in concluding that distributed system is one of the most important system in the computing system. This system is heterogeneous in nature so it requires various types of software’s and hardware’s in forming the total system. The distributed system is much larger as well as more powerful than any type of other typical centralise system due to the fact that it has a combined capability of various distributed systems. There are various examples of distributed systems which mainly includes the computer networks, distributed database and many more. The control tasks of the operating system and the database system are much more difficult to handle by the distributed systems.

References

Agrawal, D.P. and Zeng, Q.A., 2015. Distributed system contract monitoring. The Journal of Logic and Algebraic Programming, 82(5-7), pp.186-215.

Agrawal, D.P. and Zeng, Q.A., 2015. Introduction to wireless and mobile systems. Cengage learning.

Baldoni, R., Bonomi, S. and Raynal, M., 2012. Implementing a regular register in an eventually synchronous distributed system prone to continuous churn. IEEE Transactions on Parallel and Distributed Systems, 23(1), pp.102-109.

Bobelin, L., Legrand, A., Navarro, P., Quinson, M., Suter, F. and Thiéry, C., 2012, May. Scalable multi-purpose network representation for large scale distributed system simulation. In Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on (pp. 220-227). IEEE. 

Chen, S. and Ho, D.W., 2015. Sampled?Data Approach to State Estimation Performance for Heterogeneous Distributed System with Fault. Asian Journal of control, 17(5), pp.1498-1508.

Social Issues in Ubiquitous Distributed Systems

Cheng, M.M., Shiojima, D., Isobe, T. and Shimada, R., 2012, September. Voltage control of induction generator powered distributed system using a new reactive power compensator SVC-MERS. In Power Electronics and Motion Control Conference (EPE/PEMC), 2012 15th International (pp. DS3b-7). IEEE.

Coulouris, G., Dollimore, J., Kindberg, T. and Blair, G. (2011). DISTRIBUTED SYSTEMS: Concepts and Design. 5th ed.

Garonne, V., Vigne, R., Stewart, G., Barisits, M., Lassnig, M., Serfon, C., Goossens, L., Nairz, A. and Atlas Collaboration, 2014. Rucio–The next generation of large scale distributed system for ATLAS Data Management. In Journal of Physics: Conference Series (Vol. 513, No. 4, p. 042021). IOP Publishing.

Kekatos, V. and Giannakis, G.B., 2013. Distributed robust power system state estimation. IEEE Transactions on Power Systems, 28(2), pp.1617-1626.

Kumar, P. and Garg, R., 2013. Soft-checkpointing based hybrid synchronous checkpointing protocol for mobile distributed systems. In Development of Distributed Systems from Design to Application and Maintenance (pp. 87-100). IGI Global.

Lee, P.A. and Anderson, T., 2012. Fault tolerance: principles and practice (Vol. 3). Springer Science & Business Media.

Liu, T. and Jiang, Z.P., 2013. Distributed formation control of nonholonomic mobile robots without global position measurements. Automatica, 49(2), pp.592-600.

Ota, Y., Taniguchi, H., Nakajima, T., Liyanage, K.M., Baba, J. and Yokoyama, A., 2012. Autonomous distributed V2G (vehicle-to-grid) satisfying scheduled charging. IEEE Transactions on Smart Grid, 3(1), pp.559-564.

Rajguru, A.A. and Apte, S.S., 2012. A comparative performance analysis of load balancing algorithms in distributed system using qualitative parameters. International Journal of Recent Technology and Engineering, 1(3).

Rao, R.S., Ravindra, K., Satish, K. and Narasimham, S.V.L., 2013. Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE transactions on power systems, 28(1), pp.317-325

Ricci, R., Duerig, J., Stoller, L., Wong, G., Chikkulapelly, S. and Seok, W., 2012, June. Designing a Federated Testbed as a Distributed System. In TridentCom (pp. 321-337).

Toprak-Deniz, Z., Sperling, M., Bulzacchelli, J., Still, G., Kruse, R., Kim, S., Boerstler, D., Gloekler, T., Robertazzi, R., Stawiasz, K. and Diemoz, T., 2014, February. 5.2 distributed system of digitally controlled microregulators enabling per-core DVFS for the POWER8 TM microprocessor. In Solid-State Circuits Conference Digest of Technical Papers (ISSCC), 2014 IEEE International (pp. 98-99). IEEE.

Verissimo, P. and Rodrigues, L., 2012. Distributed systems for system architects (Vol. 1). Springer Science & Business Media.

Wang, J., Zhu, H. and Gomes, N.J., 2012. Distributed antenna systems for mobile communications in high speed trains. IEEE Journal on Selected Areas in Communications, 30(4), pp.675-683.

Xu, B., Da Xu, L., Cai, H., Xie, C., Hu, J. and Bu, F., 2014. Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Transactions on Industrial Informatics, 10(2), pp.1578-1586. 

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