Title
Declarative distributed advertisement system for iDTV: an industrial experience
Abstract
When designing a distributed system, good practices like using modular architectures or applying design patterns are always desirable, but there are relevant aspects that may initially go unnoticed even if we carefully approach the task by the book. Among them, there are a number of decisions to be taken about the specifics of the communications between system nodes: the format of the messages to be sent, the desired/demanded features of the network (latency, bandwidth...), etc. In particular, one of the most common problems in distributed systems design and implementation is the definition of a good approach to node failure or netsplits management. In fact, these are concerns that, in many cases, arise once the system is already at deployment stage. Different contingency mechanisms can be proposed to solve this kind of problems, and they vary greatly from one another: choosing which and how to implement them depends not only on the technology used, but also on the communications network reliability, or even the hardware where the system will be running on. In this paper we present ADVERTISE, a distributed system for advertisement transmission to on-customer-home set-top boxes (STBs) over a Digital TV network (iDTV) of a cable operator. We use this system as a case study to explain how we addressed the aforementioned problems from a declarative point of view.
Year
DOI
Venue
2012
10.1145/2370776.2370800
PPDP
Keywords
Field
DocType
aforementioned problem,system node,industrial experience,cable operator,advertisement system,systems design,good approach,digital tv network,design pattern,communications network reliability,good practice,advertisement transmission,fault tolerance
Network partition,Software deployment,Advertising,Computer science,Software design pattern,Digital television,Bandwidth (signal processing),Fault tolerance,Modular design,Reliability (computer networking),Distributed computing
Conference
Citations 
PageRank 
References 
1
0.37
14
Authors
3
Name
Order
Citations
PageRank
Macías López161.52
Laura M. Castro25010.39
David Cabrero3476.16