Importance Of Time In Distributed Systems

Importance Of Time In Distributed Systems Time is an important and interesting issue in Distributed Systems for several reasons. First, time is a quantity we always want to measure accurately. In order to know at what time of day a particular event occurred at a particular computer, it is necessary to synchronize its clock with an authoritative, external source of time. Second, algorithms that depend upon clock synchronization have been developed for several problems in distribution; these include maintaining the consistency of distributed data, checking the authenticity of a request sent to a server and eliminating the processing of duplicate updates [1] In Centralized systems, there is no need for clock synchronization because, generally, there is only a single clock. A process gets the time by simply issuing a system call to the kernel. When another process after that tries to get the time, it will get a higher time value. Thus, in such systems, there is a clear ordering of events and there is no ambiguity about the times at which these events occur. [4] In Distributed systems, there is no global clock or common memory. Each processor has its own internal clock and its own notion of time. In practice, these clocks can easily drift apart by several seconds per day, accumulating significant errors over time. Also, because different clocks tick at different rates, they may not remain always synchronized although they might be synchronized when they start. This clearly poses serious problems to applications that depend on a synchronized notion of time. Distributed systems are subject to timing uncertainties as certain processes may lack a common notion of real time. Due to an uncertainty in message delay time, absolute process synchronization is known to be impossible for such systems The literature presents issues of timing in distributed systems, physical clocks and their synchronization problems, algorithms for synchronizing physical clocks are presented with their limitations, and also techniques for implementing logical clocks which are used to monitor the order of events without measuring the physical time at which the events occurred The concept of time Let us begin by asking this simple question; does anybody really know what time it is [3] As Lamport notes, the concept of time is fundamental to our way of thinking [7] In fact, real time helps to master many problems of our decentralized real world. Time is also a useful concept when considering possible causality. Consider a person suspected of a crime, if that person has an alibi because he or she was far enough away from the site of the crime at some instant close enough to the time of the crime, then he or she cannot be the culprit. Timing problems Accurate time is important to determining the order in which events occur; [3] this is a basic standard of transactional integrity, system and networkà ¢Ã¢â€š ¬Ã‚ wide logging, auditing, troubleshooting and forensics. Having an accurate time source plays a critical role in tracing and debugging problems that occur on different platforms across a network. Events must be correlated with each other regardless of where they were generated. Furthermore, the notion of time (or time ranges) is used in many forms of access control, authentication, and encryption. In some cases, these controls can be bypassed or rendered inoperative if the time source could be manipulated. For example, a payroll function could be tricked into providing access over a weekend when normally it would be restricted to normal business hours. [3] Physical clocks Most computers today keep track of the passage of time with a battery-backed up Complementary Metal Oxide Semiconductor (CMOS) clock circuit, driven by a quartz resonator. This allows the timekeeping to take place even if the machine is powered off. When on, an operating system will generally program a timer circuit (a Programmable Interval Timer, or PIT, in older Intel architectures and Advanced Programmable Interrupt Controller, or APIC, in newer systems.) to generate an interrupt periodically (common times are 60 or 100 times per second). The interrupt service procedure simply adds one to a counter in memory. While the best quartz resonators can achieve an accuracy of one second in 10 years, they are sensitive to changes in temperature and acceleration and their resonating frequency can change as they age. Standard resonators are accurate to 6 parts per million at 31 °C, which corresponds to  ±Ãƒâ€šÃ‚ ½ second per day. The problem with maintaining a concept of time is when multiple entities expect each other to have the same idea of what the time is. Two watches hardly ever agree. Computers have the same problem: a quartz crystal on one computer will oscillate at a slightly different frequency than on another computer, causing the clocks to tick at different rates. The phenomenon of clocks ticking at different rates, creating an ever widening gap in perceived time is known as clock drift. The difference between two clocks at any point in time is called clock skew and is due to both clock drift and the possibility that the clocks may have been set differently on different machines. The Figure below illustrates this phenomenon with two clocks, A and B, where clock B runs slightly faster than clock A by approximately two seconds per hour. This is the clock drift of B relative to A. At one point in time (five seconds past five oclock according to As clock), the difference in time between the two clocks is approximately four seconds. This is the clock skew at that particular time. Compensating for drift We can envision clock drift graphically by considering true Coordinated Universal Time (UTC) flowing on the x-axis and the corresponding computers clock reading on the y-axis. A perfectly accurate clock will exhibit a slope of one. A faster clock will create a slope greater than unity while a slower clock will create a slope less than unity. Suppose that we have a means of obtaining the true time. One easy (and frequently adopted) solution is to simply update the system time to the true time. To complicate matters, one constraint that well impose is that its not a good idea to set the clock back. The illusion of time moving backwards can confuse message ordering and software development environments. If a clock is fast, it simply has to be made to run slower until it synchronizes. If a clock is slow, the same method can be applied and the clock can be made to run faster until it synchronizes. The operating system can do this by changing the rate at which it requests interrupts. For example, suppose the system requests an interrupt every 17 milliseconds (pseudo-milliseconds, really the computers idea of what a millisecond is) and the clock runs a bit too slowly. The system can request interrupts at a faster rate, say every 16 or 15 milliseconds, until the clock catches up. This adjustment changes the slope of the system time and is known as a linear compensating Function. After the synchronization period is reached, one can choose to resynchronize periodically and/or keep track of these adjustments and apply them continually to get a better running clock. This is analogous to noticing that your watch loses a minute every two months and making a mental note to adjust the clock by that amount every two months (except the system does it continually). Synchronizing physical clocks With physical clocks, our interest is not in advancing them just to ensure proper message ordering, but to have the system clock keep good time. We looked at methods for adjusting the clock to compensate for skew and drift, but it is essential that we get the time first so that we would know what to adjust. One possibility is to attach a GPS (Global Positioning System) receiver to each computer. A GPS receiver will provide time within  ± 1 msec. of UTC time but Unfortunately, they rarely work indoors. Alternatively, if the machine is in the U.S., one can attach a WWV radio receiver to obtain time broadcasts from Texas, Colorado or Washington, DC, giving accuracies of  ± 3-10 msec. depending on the distance from the source. Another option is to obtain a GOES (Geostationary Operational Environment Satellites) receiver, which will provide time within  ± 0.1 msec. of UTC time. For reasons of economy, convenience, and reception, these are not practical solutions for every machine. Most machines will set their time by asking another machine for the time (preferably one with one of the aforementioned time sources). A machine that provides this information is called a time server. Several algorithms have been proposed for synchronizing clocks and they all have the same underlying model of the system Cristians algorithm The simplest algorithm for setting the time would be to simply issue a remote procedure call to a time server and obtain the time. That does not account for the network and processing delay. We can attempt to compensate for this by measuring the time (in local system time) at which the request is sent (T0) and the time at which the response is received (T1). Our best guess at the network delay in each direction is to assume that the delays to and from are symmetric (we have no reason to believe otherwise). The estimated overhead due to the network delay is then (T1- T0)/2. The new time can be set to the time returned by the server plus the time that elapsed since the server generated the timestamp: Suppose that we know the smallest time interval that it could take for a message to be sent between a client and server (either direction). Lets call this time Tmin. This is the time when the network and CPUs are completely unloaded. Knowing this value allows us to place bounds on the accuracy of the result obtained from the server. If we sent a request to the server at time T0, then the earliest time stamp that the server could generate the timestamp is T0 + Tmin. The latest time that the server could generate the timestamp is T1 Tmin, where we assume it took only the minimum time, Tmin, to get the response. The range of these times is: T1 T0 2Tmin, so the accuracy of the result is: Errors are cumulative. If machine A synchronizes from a server B and gets an accuracy of  ±5 msec but server B in turn got its time from server C with an accuracy of  ±7 msec, the net accuracy at machine A is  ±(5+7), or  ±12 msec. Several time requests may be issued consecutively in the hope that one of the requests may be delivered faster than the others (e.g., it may be submitted during a time window when network activity is minimal). This can achieve improved accuracy. Cristians algorithm suffers from the problem that afflicts all single-server algorithms: the server might fail and clock synchronization will be unavailable. It is also subject to malicious interference. Berkeley algorithm The Berkeley algorithm, developed by Gusella and Zatti in 1989 [8], is form of an internal synchronization that does not assume that any machine has an accurate time source with which to synchronize. Instead, it opts for obtaining an average time from the participating computers and synchronizing all machines to that average. The machines involved in the synchronization each run a time dà ¦mon process that is responsible for implementing the protocol. One of these machines is elected (or designated) to be the master. The others are slaves. The server polls each machine periodically, asking it for the time. The time at each machine may be estimated by using Cristians method to account for network delays. When all the results are in, the master computes the average time (including its own time in the calculation). The hope is that the average cancels out the individual clocks tendencies to run fast or slow. Instead of sending the updated time back to the slaves, which would introduce further uncertainty due to network delays, it sends each machine the offset by which its clock needs adjustment. The operation of this algorithm is illustrated in the Figure below. Three machines have times of 3:00, 3:25, and 2:50. The machine with the time of 3:00 is the server (master). It sends out a synchronization query to the other machines in the group. Each of these machines sends a timestamp as a response to the query. The server now averages the three timestamps: the two it received and its own, computing (3:00+3:25+2:50)/3 = 3:05. Now it sends an offset to each machine so that the machines time will be synchronized to the average once the offset is applied. The machine with a time of 3:25 gets sent an offset of -0:20 and the machine with a time of 2:50 gets an offset of +0:15. The server has to adjust its own time by +0:05. The algorithm also has provisions to ignore readings from clocks whose skew is too great. The master may compute a fault-tolerant average averaging values from machines whose clocks have not drifted by more than a certain amount. If the master machine fails, any other slave could be elected to take over Logical clocks Lets again consider cases that involve assigning sequence numbers (timestamps) to events upon which all cooperating processes can agree. What matters in these cases is not the time of day at which the event occurred but that all processes can agree on the order in which related events occur. Our interest is in getting event sequence numbers that make sense system-wide. If we can do this across all events in the system, we have something called total ordering: every event is assigned a unique timestamp (number), every such timestamp is unique. However, we dont always need total ordering. If processes do not interact then we dont care when their events occur. If we only care about assigning timestamps to related (causal) events then we have something known as partial ordering. Leslie Lamport [7] developed a happened before notation to express the relationship between events: aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b means that a happened before b. If a represents the timestamp of a message sent and b is the timestamp of that message being received, then aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b must be true; a message cannot be received before it is sent. This relationship is transitive. If aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b and bà ¢Ã¢â‚¬  Ã¢â‚¬â„¢c then aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢c. If a and b are events that take place in the same process the aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b is true if a occurs before b. The importance of measuring logical time is in assigning a time value to each event such that everyone will agree on the final order of events. That is, if aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b then clock (a) < clock (b) since the clock (our timestamp generator) must never run backwards. If a and b occur on different Processes that do not exchange messages (even through third parties) then aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b is not true, these events are said to be concurrent: there is no way that a could have influenced b. Each event is assigned a timestamp by its respective process. The process simply maintains a global counter that is incremented before each event gets a timestamp. If we examine the timestamps from our global perspective, we can observe a number of peculiarities. Event g, the event representing the receipt of the message sent by event a, has the exact same timestamp as event a when it clearly had to take place after event a. Event e has an earlier time stamp (1) than the event that sent the message (b, with a timestamp of 2). Lamports algorithm Lamport [7] proposed an algorithm that forces the resequencing of timestamps to ensure that the happened before relationship is properly depicted for events related to sending and receiving messages. It works as follows: Each process has a clock, which can be a simple counter that is incremented for each event. The sending of a message is an event and each message carries with it a timestamp obtained from the current value of the clock at that process (sequence number). The arrival of a message at a process is also an event will also receive a timestamp by the receiving process, of course. The process clock is incremented prior to time stamping the event, as it would be for any other event. If the clock value is less than the timestamp in the received message, the systems clock is adjusted to the (messages timestamp + 1). Otherwise nothing is done. The event is now time stamped. If we apply this algorithm to the same sequence of messages, we can see that proper message ordering among causally related events is now preserved. Note that between every two events, the clock must tick at least once. [4] Lamports algorithm [7] allows us to maintain proper time ordering among causally- related events. In summary, Lamports algorithm requires a monotonically increasing software counter for a clock that has to be incremented at least when events that need to be time stamped take place. These events will have the clock value, or Lamport timestamp, associated with them. For any two events, where aà ¢Ã¢â‚¬  Ã¢â‚¬â„¢b, L (a) < L (b) where L(x) represents the Lamport timestamp for event x. Lamport timestamps [7] assure us that if there is a causal relationship between two events, then the earlier event will have a smaller time stamp than the later event. Causality is achieved by successive events on one process or by the sending and receipt of messages on different processes. As defined by the happened-before relationship, causality is transitive. For instance, events a and f are causally related in the figure above (through the sequence a, b, e, f). Implementing Logical clocks To implement logical clocks, [11] each process p, maintains data structures that give it the following two capabilities: A logical clock, denoted by C, that helps P, measure its own progress; and A global logical clock denoted by gC, that represents Ps local view of the global logical time. A protocol is presented to update the data structures; the protocol ensures that a processs logical clock and its view of the global time are consistent. The protocol consists of the following two rules: R1. maintains how a process updates the local logical clock when it executes an Event, whether send or receive R2. maintains how a process updates its global logical clock to update its view of the Global time. It dictates what information about the logical time a process Piggybacks in a message and how the receiving process uses this information to Update its view of the global time A distributed system consisting of logical clocks differ in their representation of logical time and in the protocol for updating logical clocks. However, all systems consisting of logical clocks implements some form of R1 and R2 and thereby achieving the fundamental monotonicity property associated with events and casualty Total ordering of events Note that it is very possible for multiple non-causal (concurrent) events to share identical Lamport timestamps (e.g., c, e, and h in the Figure above). This may cause confusion if multiple processes need to make a decision based on the timestamps of two events. The selection of a specific event may not matter if the events are concurrent but we want all the processes to be able to make the same decision. This is difficult if the timestamps are identical. Fortunately, theres an easy remedy. We can create a total order on events by further qualifying them with identities of processes. We define a global logical timestamp (Ti,i) where Ti represents the local Lamport timestamp and i represents the process ID (in some globally unique way: for example, a concatenation of host address and process ID). We are then able to globally compare these timestamps and conclude that There is no physical significance to the order since process identifiers can be arbitrary and do not relate to event ordering but the ability to ensure that no two Lamport timestamps are the same globally is helpful in algorithms that need to compare these timestamps. In real life, depending on the application, one may use a combination of thread ID, process ID, and IP address as a qualifier to the timestamp. Vector clocks If two events are causally related and event e happened before event e then we know that L (e) < L (e). However, the converse is not necessarily true. With Lamports algorithm, if L (e) < L (e) we cannot conclude that eà ¢Ã¢â‚¬  Ã¢â‚¬â„¢e. Hence, if we look at Lamport timestamps, we cannot conclude which pairs of events are causally related and which are not. One solution that has been proposed to deal with this problem is the concept of vector clocks (proposed by Mattern in 1989 and Fidge in 1991) [9, 10]. A vector clock in a system of N processes is a vector of N integers. Each process maintains its own vector clock (Vi for a process Pi) to timestamp local events. Like Lamport timestamps, vector timestamps (the vector of N integers) are sent with each message. The rules for using vector clocks are: The vector is initialized to 0 at all processes: Vi[j] = 0 for i,j = 1, à ¢Ã¢â€š ¬Ã‚ ¦, N Before a process Pi timestamps an event, it increments its element of the vector in its local vector: Vi[i] = Vi[i]+1 A message is sent from process Pi with Vi attached to the message. When a process Pj receives a vector timestamp t, it compares the two vectors element by element, setting its local vector clock to the higher of the two values: Vj[i] = max(Vj[i], t[i]) for i=1, à ¢Ã¢â€š ¬Ã‚ ¦, N We compare two vector timestamps by defining: V = V iff V[j] = V'[j] for i=1, à ¢Ã¢â€š ¬Ã‚ ¦, N V à ¢Ã¢â‚¬ °Ã‚ ¤ V iff V[j] à ¢Ã¢â‚¬ °Ã‚ ¤ V'[j] for i=1, à ¢Ã¢â€š ¬Ã‚ ¦, N For any two events e, e, if eà ¢Ã¢â‚¬  Ã¢â‚¬â„¢e then V(e) < V(e). This is the same as we get from Lamports algorithm. With vector clocks, we now have the additional knowledge that if V(e)

Big Foot

The Mystery of Bigfoot Bigfoot is unquestionably North America’s biggest crypto zoological mystery. The idea of Bigfoot has been around for hundreds of years, its history and possible sightings have been documented for years on end. Throughout history, man has battled the topic of Bigfoot and if this creature really does exists. Researchers have found arguable evidence, and numerous sightings have been reported throughout North America. Then again, roughly 70% of sightings reported are a misidentification.Bigfoot supposedly inhabits forests mainly in the Pacific Northwest region of North America. Scientists discount the existence of Bigfoot and consider it to be a combination of  folklore, misidentification, and  hoax, rather than a living animal. So the question remains, is the existence of this creature fact or fiction? So where does the name â€Å"Bigfoot† come anyway? It is said that this Indian-sounding word was coined in the 1920’s by J. W. Burns, a tea cher who for fours years collected stories about wild, hairy giants from his Chehalis Indian friends.Burns combined several similar Native Canadians’ names for these creatures and created the word â€Å"Sasquatch†. In recent years, scientists and folklorists looking to bring respectability to the subject but most North Americans still use the name â€Å"Bigfoot†. The first use of the now widely used label did not occur until a construction worker named Jerry Crew appeared at a northern California newspaper office with a cast of the alleged Bigfoot’s foot found in the mud in Bluff Creek Valley.Hundreds of people have reported seeing the Bigfoot or it’s footprints but none have physical evidence to back up their stories. They describe the creature as standing from seven to ten feet tall and weighing more than six hundred pounds. The distinctive footprint shows a track as left by a giant five toed human foot. The average length is fourteen to sixteen inches long. The most controversial evidence of Bigfoot's existence is the infamous Patterson video. It was filmed in 1967 near Bluff Creek California. By Roger Patterson, an amateur Bigfoot hunter and rodeo cowboy.In the video, which was filmed in a dry creek bed, Bigfoot appears to be walking along the creek bed, and at one point even stared at the camera. The footage has been analyzed many times by scientists, some of which say the footage is realistic while others do not. Many times when people see something like Bigfoot they think that they will be ridiculed by their friends and neighbors, so they keep there encounter secret for many years. Until others tell their stories. The top three questions that come into some ones mind when they hear about Bigfoot are â€Å"is he man, myth or creature? . Many do not believe of such a creature lurking the forests and are uneducated on the topic so they come to the quick conclusion that someone disguised himself in a costume for attention perhaps. The majority believes strongly that Bigfoot is evidently a myth or hoax for the simple logic that there is not enough evidence to prove Bigfoot’s existence. The most arguable evidence are footprints that can be easily replicated to furthermore puzzle scientists. Also, the lack of carcasses and excrements just don’t add up.Lastly, the big question of is it just a creature which means every sighting would have to be a misidentification. Scientists do believe and have partial evidence that Bigfoot could be a relative with an ancient ape named â€Å"Gigantopithecus†. Then again, some footprints have been reported with claw marks, which could be a grizzle bear. Many can speculate the existence of Bigfoot but until a body is scientifically examined, the riddle of Bigfoot will continue as one of cryptozoology’s biggest and most famous enigmas. Even if Bigfoot is just one big hoax, the myth will live on forever.

Macbeth Downfall Essay

A good description of the character Macbeth from an unknown author: â€Å"I am my own worst enemy and I can never win the fight† (www. searchquotes. com). This quote describes Macbeth’s fighting for the throne and his failure in doing so. The main character, Macbeth, and his wife, Lady Macbeth, plot together to kill their king and take over the throne. Their success is short lived when the guilt of this evil act takes its toll on Lady Macbeth ultimately ending in her demise and Macbeth steers him self towards his own downfall. Macbeth makes bad decisions during the play that all snowball into a final battle. A question that is regularly thrown up in the air for debate is- Who is Responsible for Macbeth’s downfall? Some critics believe that it was Lady Macbeth that led Macbeth on the road to failure. Seeing how she is the one who forcefully prods Macbeth into murdering Duncan; However, it is Macbeth who suggests that they take advantage of their golden opportunity and Lady Macbeth just keeps him on track with their devious plan. In fact when one looks at who is the most responsible for Macbeth’s downfall, it is Macbeth because he was the first to think about killing Duncan, he killed Banquo, and he murdered Macduff’s family. To begin, some might argue that it is Lady Macbeth who is the main reason for Macbeth’s downfall. After receiving the message from Macbeth about his prophecy given to him by the three witches he tells her that they should kill Duncan when he come over to their castle. When Macbeth is considering to not kill Duncan lady Macbeth threatens him with: â€Å"I would, while it was smiling in my face,/ Have plucked my nipple from his boneless gums/ And dashed the brains out, had I so sworn as you/ Have done to this† (I. vii. 57-60). To some critics this line is the shove that Lady Macbeth gives Macbeth to his downfall. This is just one interpretation of who is at fault, the evidence from Act I shows that it is really Macbeth who is at fault. The three witches have just given Macbethand Banquo their prophecies. Macbeth is thinking about what the witches have told him: â€Å"If good, why do I yield to that suggestion/ Whose horrid image doth unfix my hair† (I. iii. 138-139). This is Macbeth realizing that his first thought after finding out that the first prophecy came true and what he will have to do for the second one to come true. Macbeth caused his own downfall by thinking about killing Duncan and then sharing those thoughts with Lady Macbeth. If Macbeth never had the thought of taking fate into his own hands then he would not have told Lady Macbeth and would not have had his horrific downfall. That is why he is the one responsible for his own demise. Firstly, Macbeth caused his own downfall by killing King Duncan. His thoughts about killing Duncan started his downward spiral to his own death. Macbeth is a very malicious character bound for self destruction while taking others who were close to him, with him. Macbeth’s first instinct when given the prophecies is to murder for his own personal gain. Macbeth is still thinking over whether or not to kill Duncan when he says: â€Å"Is this a dagger which I see before me,/ The handle toward my hand? Come, let me clutch thee† (II. i. 33-35). This quote shows that subconsciously he wants to kill Duncan for the throne. Even though he is weary about the murder his subconscious is telling him that it is the right thing to do and that he will be better off as king. Macbeth is convincing himself to kill Duncan, which shows that he is the reason for his downfall by starting a chain of events that lead to his death. Macbeth also raises suspicion from Banquo by killing Duncan because Banquo heard the prophecy of being king as well. Banquo is leaving Macbeth’s castle when he says: â€Å"Thou hast it now: king, Cawdor, Glamis, all,/ As the weird women promised, and I fear/ Thou played’st most foully for ’t† (III. i. 1-3). This quote is Banquo saying that he suspects that Macbeth has cheated Duncan from the throne. This adds to Macbeth being his own worse enemy because now he has created a loose end because Banquo knows about the prophecy given to him. This is another reason why Macbeth caused his own downfall. Secondly, Macbeth adds to his own downfall by trying to clean up after himself by getting rid of Banquo and Fleance whom he fears knows about him killing King Duncan. Macbeth is worried about the truth of the murder getting out so he takes matters into his own hands by hiring three murderers to find and kill Banquo and Fleance before they can tell anyone of the terrible truth about Duncan’s untimely death. Macbeth fears Banquo because Banquo suspect’s foul play in Macbeth’s becoming of king. Macbeth shows his fear of him right after he and Fleance leave Macbeth’s castle: â€Å"There is none but he/ Whose being I do fear† (III. i. 56-57). In this quote Macbeth is talking about Banquo and how he fears that he knows that he murdered Duncan to become king. Macbeth supects that Banquo knows this because he was with him when the three witches came and gave Macbeth the prophecy of becoming king. Because of the prophecy that was given to Banquo, he would not be king but his son would start a line of kings, this means that Macbeth must be overthrown for Fleance to be king. Macbeth sends people to kill Banquo and Fleance because he does not want the prophecy to become reality because this would mean his death. Macbeth knows that he has made it easier for Fleance to be king when he says: â€Å"For them the gracious/ Duncan have I murdered:/†¦ To make them kings, the seed of Banquo kings! † (III. i. 68,72). Macbeth has killed Duncan and assumed the role of king but once Banquo tells people that Macbeth has killed Duncan then there will be an uprising against Macbeth, which may end in him dying. If Duncan were still alive then Fleance would not have a chance to become king and Macbeth would not have created his own downfall. Lastly, Macbeth goes out of his way to murder Macduff’s family because he did not attend his coronation. This leads to Macduff grieving over his loss and Malcolm trying to turn his sorrow into vengeance. Malcolm convinces Macduff to seek revenge on Macbeth by telling Macduff: â€Å"Be comforted. / Let’s make us med’cines of our great revenge,/ To cure this deadly grief† (IV. iii. 219-221). Malcolm is telling Macduff to use revenge to help mend his broken heart from the death of his family. Malcolm wants to seek revenge on Macbeth for killing is father and stealing the throne and wants Macduff to do the same. Macduff agrees with Malcolm and they set out to kill Macbeth for his treachery. By killing Macduff’s family, Macbeth only gave Macduff a reason to kill him. There was no need to kill Macduff’s family that is why Macbeth is at fault for his own downfall and no one else. To conclude, Macbeth’s downfall is entirely his own fault. Firstly his malicious side comes out and he kills King Duncan, then he proceeds to try and clean up his mess by getting rid of suspicions which goes unsuccessful, and finally he murders Macduff’s family which gave Macduff reason to kill him. That is how Macbeth caused his own downfall and is why he is entirely at fault. The outcome may have been different if it were not for all three events happening. Because these events occurred lives were lost for nothing seeing as Macbeth lost the throne and died in the end. Why does Macbeth kill Macduff’s family? Get an answer by ordering custom essay.

Essay about Religious Toleration during the Enlightenment

The Enlightenment of the 18th century evolved due to the many changes brought about by the Scientific Revolution. With all of the new scientific discoveries, new thought processes were developed. The scientists of the Scientific Revolution brought about revolutionary change. These scientists inspired the philosophes of the Enlightenment to challenge the ways of the Old Regime and question the ideas of the church. Philosophers such as Francois Voltaire, Jean-Jacques Rousseau, and John Locke published their controversial ideas and these ideas along with some important political action, helped to mold a new type of society. The new society was one that tolerated different religious beliefs. The minds of men, abandoning the old disciplines†¦show more content†¦This caused many problems because Protestants and Catholics could not live together peacefully. Individuals from both religions did not see the others view. This was one reason that the Enlightenment was needed. Because th e members of each religion resented each other so much, many wars were fought. This also brought about new questions as to which religion had the correct beliefs. The religion that was practiced was dependent upon the country, and the leader of that country.4 The Glorious Revolution of 1688, the Toleration Act of 1689, and the English Bill of Rights of 1689 were major political actions that helped to establish religious freedoms. These political actions established that the Crown could not have a standing army or levy taxes on the citizens without the permission of Parliament. They also abolished the concept of the divine right of kings and extreme religious persecution. Before the Glorious Revolution, the Toleration Act, and the English Bill of Rights, the King or Queen was able to mandate a universal religion for all of the nation’s citizens. This caused a lot of turmoil within the nation and caused it to stand divided. With more citizens beginning toShow MoreRelatedPowerful Enlightened Depots841 Words   |  3 Pages18th century in which absolute monarchs pursued legal, social, and educational reforms inspired by the Enlightenment (The Editors of Encyclopaedia Britannica). The magnitude of the philosophy movement known as the E nlightenment sent ripples throughout Western society. The philosophers believed that in order to improve society they had to enlighten the monarchs. The views of the Enlightenment did to find their way inside the palaces of Europes leaders; however, the monarchs retained their greatRead MoreThe, Gift Of God s Grace1284 Words   |  6 Pages17.3 Joseph II of Austria, Toleration Patent 1781, pogroms, Pietism, John Wesley, Methodism, â€Å"gift of God’s grace† 1) Joseph II of Austria. Joseph II of Austria was emperor of the Holy Roman Empire from 1765 to 1790, and served as ruler of Habsburg from 1780 to 1790. 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