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FiWi access networks based on next-generation PON and gigabit-class WLAN technologies

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Fiber-Wireless (FiWi) access networks

Email or Customer ID. Forgot password? Old Password. New Password. Password Changed Successfully Your password has been changed. In this way legacy PSM saves energy consumption by having the provision of sleep state. However buffering the data at AP during sleep state introduces buffering delay, which need to be considered. In PSM a beacon interval consists of two states namely sleep and active states. The overall energy consumption is given by-.

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Since sleep state consumes less energy than active state; all previous works emphasize on increasing the sleeping opportunity of the device and making it energy efficient. However energy consumption during active state may also play crucial role, which has not been addressed so far. This subsection analyses various factors affecting the energy consumption during active state. Front end sub-network is considered as IEEE In active state, energy consumption depends on T ac and P ac. IEEE Another factor affecting active state energy consumption is P ac. The necessary active power for a certain service requirement depends on various factors like the transmission rate, the distance between communicating devices, the channel characteristics etc.

For a time invariant channel with fixed distance between transmitter and receiver estimated active power consumption is used for analysis. Let P o be the estimated power consumption for transmission of one packet with minimum possible data rate that is 6 Mbps then active state energy consumption at different data rates for a single packet can be calculated and given in table II [ 17 ]. It can be seen from table II that lower data rate needs more time to transmit the data but requires less transmit power. Hence energy consumption is reduced by transmission on lower data rate than the higher data rate.

However most of the work done so far tries to increase sleeping to gain energy efficiency. For considered network we can also caculate energy required during sleep state. For the beacon interval of ms, T sl can be calculated as:. Similar to the active state, sleep state energy consumption at different data rates for a single packet with constant sleep power P sl , can be calculated and is given in table III. It can be observed from table that transmission on higher data rates provide more sleeping opportunity but values of sleeping time is not significantly reduced as data rates are increased.

Therefore reduction in energy consumption due to more sleeping opportunity is not very significant. On the other hand, it is evident from table II that energy consumption in active state has major impact on data rate. Higher the data rate more is the energy consumption. So proposed algorithm tries to save the energy during active state and transmits the data on lower data rate without affecting the performance in terms of delay.

This significantly increases the energy efficiency at front end of FiWi network. Transmission on lower data rate consumes less energy as compared to higher data rate. The proposed algorithm mainly focuses on selecting lower data rate while maintaining transmission delay within specified limit during active state of a beacon interval from the set of available data rates for IEEE standard Minimum data rate on which transmission takes place within prescribed transmission delay is called optimal data rate.

This facilitates reduction in active state energy consumption of front end. For considering fixed energy consumption at back-end, proposed approach will contribute to significant reduction in overall energy consumption with maintaining the quality of service in terms of transmission delay of FiWi network. Subsection A gives the various notations used in energy efficient rate adaptive algorithm. Rate adaptation is applied to modify the existing PSM for further reduction in energy consumption of active state of a beacon interval.

In general data transmission is carried out with highest possible data rate, so that device can get more sleeping opportunities with minimum transmission delay. The EERAA proposes the adaptive data rate for transmission, which is the function of previous traffic arrival pattern. This facilitates the data transmission at lower possible data rates as compared to fixed higher data rate transmission.

This results in reduction in energy consumption of a complete beacon interval. The different parameters used in proposed algorithm are as follows:. It is the minimum time required to transmit the data when the system is operated on maximum possible data rate and can be given by-. It is the data rate which is calculated on the basis of traffic arrival pattern of previous N beacon intervals. Let B avg be the average buffer data, then the future estimated rate is given as:.

This section presents the simulation results showing comparison of energy consumption for various fixed data rate schemes and EERAA. Fixed data rate scheme refers to transmission on one fixed rate. We have considered IEEE In this system data is transmitted on highest possible data rate, to increase the sleeping opportunities. The system switches to lower data rate only in case of either poor channel quality or distance between transmitter and receiver get increased.

Transmission on higher data rate consumes more active state energy. Therefore our algorithm tries to save the energy during active state and can transmit the data on lower data rate without affecting the performance in terms of delay. In this way it is possible to achieve trade-off between energy consumption and transmission delay.

For simulation a fixed distance point to point link between an AP and a router has been considered. Rate assignment or switching is completely based on future estimated rate by previous packet arrival pattern, delay constrain for specific service and current queue size. For simulation following parameters are considered as shown in table IV. Simulation started from end of the beacon interval i. The estimated rate for the current queue size decides the current link rate.

This current link rate either increases or decreases from its current value according to the traffic arrival pattern. It can be shown that the current data rate of the link can be incremented by the value of next index or decremented by value of previous index from standard set of data rates. The purpose of rate switching in the EERAA is to reduce the energy consumption during active period that will be clear from the subsequent results. In order to compare energy consumption for proposed EERAA and various fixed data rate schemes, energy consumption during active state and sleep state is calculated.

The total energy consumption for different traffic load is shown in fig. It can be seen that the total energy consumed for data transmission at 54 Mbps scheme is maximum whereas it is minimum at 24Mbps scheme. EERAA maintains the data rate in between 24 Mbps and 54 Mbps schemes according to the accumulated load in buffer, such that the buffer will empty completely within the predefined delay. This will reduce the overall energy without affecting the delay performance of the network.

Similarly energy consumption for active state, sleep state and overall energy consumption for different fixed data rate schemes and EERAA is compared in fig.

Fiber-Wireless (FiWi) Access Networks: Challenges and Opportunities

As the energy consumption during sleep state is already very less and almost same for all the schemes, the active state energy consumption plays an important role in the total energy consumption. The EERAA effectively reduces total energy consumption during a beacon interval which is clear from fig. It is well known that lower data rate scheme requires more transmission delay as compared to high data rate scheme contrarily high data rate schemes transmit the data rapidly, but require more active energy consumption.

On the other hand EERAA tries to maintain tradeoff between required transmission delay and active energy consumption which is clear from fig. Hence EERAA gives a better trade-off for delay and energy consumtion as compared to various fixed data rates schmes.


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The proposed algorithm tries to reduce energy consumption of front end of FiWi network during active state of transmission by using the concept of rate adaptation method. Although, the principle of rate adaptation is widely used to maintain quality of transmission in case of poor channel conditions. But, its application is novel for reducing energy consumption during active state of transmission.

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It also maintains transmission delay within specified tolerable limit. Hence it may offer great candidature as energy efficient technique among various existing techniques for FiWi access networks. Bhatt, N. Chouhan, R. Shaddad, A. Mohammad, S. Al-Gailani, A.

Energy Efficient Rate Adaptation Algorithm for FiWi Access Network

Al-hetar, M. Ghazisaidi and M. Kazovsky, T.