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Polar codes are a class of capacity-achieving codes for the binary-input discrete memoryless channels (B-DMCs). However, when applied in channels with intersymbol interference (ISI), the codes may perform poorly with BCJR equalization and conventional decoding methods. To deal with the ISI problem, in this paper a new joint successive cancellation (SC) decoding algorithm is proposed for polar codes in ISI channels, which combines the equalization and conventional decoding. The initialization information of the decoding method is the likelihood functions of ISI codeword symbols rather than the codeword symbols. The decoding adopts recursion formulas like conventional SC decoding and is without iterations. This is in contrast to the conventional iterative algorithm which performs iterations between the equalizer and decoder. In addition, the proposed SC trellis decoding can be easily extended to list decoding which can further improve the performance. Simulation shows that the proposed scheme significantly outperforms the conventional decoding schemes in ISI channels.

Constructing composite services by using of services offered by third parties is an attractive and inexpensive way for service brokers and aggregators to enhance differentiation from their competitors. When multiple services provide the same or similar functionalities, selecting those that satisfy users' non-functional requirements is crucial. In many cases, non-functional properties of services are heavily dependent on the activity of the network delivering those services whilst the network activity follows certain time-sensitive rules. We present a service selection algorithm that takes into account time-sensitive variations of non-functional propensities of services to identify a service combination offering the highest quality within a specified time interval.

Constructing composite services by using of services offered by third parties is an attractive and inexpensive way for service brokers and aggregators to enhance differentiation from their competitors. When multiple services provide the same or similar functionalities, selecting those that satisfy users' non-functional requirements is crucial. In many cases, non-functional properties of services are heavily dependent on the activity of the network delivering those services whilst the network activity follows certain time-sensitive rules. We present a service selection algorithm that takes into account time-sensitive variations of non-functional propensities of services to identify a service combination offering the highest quality within a specified time interval.

Constructing composite services by using of services offered by third parties is an attractive and inexpensive way for service brokers and aggregators to enhance differentiation from their competitors. When multiple services provide the same or similar functionalities, selecting those that satisfy users' non-functional requirements is crucial. In many cases, non-functional properties of services are heavily dependent on the activity of the network delivering those services whilst the network activity follows certain time-sensitive rules. We present a service selection algorithm that takes into account time-sensitive variations of non-functional propensities of services to identify a service combination offering the highest quality within a specified time interval.

Constructing composite services by using of services offered by third parties is an attractive and inexpensive way for service brokers and aggregators to enhance differentiation from their competitors. When multiple services provide the same or similar functionalities, selecting those that satisfy users' non-functional requirements is crucial. In many cases, non-functional properties of services are heavily dependent on the activity of the network delivering those services whilst the network activity follows certain time-sensitive rules. We present a service selection algorithm that takes into account time-sensitive variations of non-functional propensities of services to identify a service combination offering the highest quality within a specified time interval.

Constructing composite services by using of services offered by third parties is an attractive and inexpensive way for service brokers and aggregators to enhance differentiation from their competitors. When multiple services provide the same or similar functionalities, selecting those that satisfy users' non-functional requirements is crucial. In many cases, non-functional properties of services are heavily dependent on the activity of the network delivering those services whilst the network activity follows certain time-sensitive rules. We present a service selection algorithm that takes into account time-sensitive variations of non-functional propensities of services to identify a service combination offering the highest quality within a specified time interval.