The problem:
From the firsts centralized, "dumb" terminal based interfaces to the actual cloud computing with rich interfaces almost everything changed, interfaces, database software, operating systems, computer architecture layers, communication protocols, but in my point of view the big change is how users have access to the system functionality. In older mainframes someone that wants to run a program and receive the output as a printed list, should submit a batch request and way for free machine time to run, forms are written in paper sheets and then typed into system screen by computing skilled people. With the evolution of technology, part of the computing power goes to the user desktop, with client-server architecture but it still need software installed in his machine by some skilled person, this takes time and generates complexity in the environment and now we have the HTTP protocol that change radically how user obtain access to some system, he just need a network connection and a very generic software, one internet browser software.
So the mainframe architecture provides a very predictive demand planning, only those connected terminals can generate processing demands on the server, with the "opening" of the systems more users can easily reach the system and use it when it needs, this, in the user point of view is much better than job schedulers, but to the administration point of view generates lots of problems, with one internet open system is no more possible predict how many users will use the system in certain point of time, how much processing power will be needed to handle all requests, a concept of capacity planning becomes more and more important. Companies that handle with global customers does anymore nightly maintenance, always is day somewhere.
Proposed solution:
The tissue computing paradigm addressed this problem by design, the idea of a system that grow by demand and learn with his own history, ensures that the management of processing capacity is no more a (humans) system administrations but a system function, the tissue should be able to detect and react or forecast and prevent processing shortage and processing wastage situations.
Using this approach for system paradigm is feasible use big datacenters and rent resources for many tissues that coexists time-sharing resources as needed. Some classical cases that this is very useful are season changing behaviors like hotel systems and commerce system just before Christmas. Or some "sun following" systems that have more usage while this in its timezone and less while night.
The key features to solve this question are service migration, service scaling and service high availability in the tissue.
From the firsts centralized, "dumb" terminal based interfaces to the actual cloud computing with rich interfaces almost everything changed, interfaces, database software, operating systems, computer architecture layers, communication protocols, but in my point of view the big change is how users have access to the system functionality. In older mainframes someone that wants to run a program and receive the output as a printed list, should submit a batch request and way for free machine time to run, forms are written in paper sheets and then typed into system screen by computing skilled people. With the evolution of technology, part of the computing power goes to the user desktop, with client-server architecture but it still need software installed in his machine by some skilled person, this takes time and generates complexity in the environment and now we have the HTTP protocol that change radically how user obtain access to some system, he just need a network connection and a very generic software, one internet browser software.
So the mainframe architecture provides a very predictive demand planning, only those connected terminals can generate processing demands on the server, with the "opening" of the systems more users can easily reach the system and use it when it needs, this, in the user point of view is much better than job schedulers, but to the administration point of view generates lots of problems, with one internet open system is no more possible predict how many users will use the system in certain point of time, how much processing power will be needed to handle all requests, a concept of capacity planning becomes more and more important. Companies that handle with global customers does anymore nightly maintenance, always is day somewhere.
Proposed solution:
The tissue computing paradigm addressed this problem by design, the idea of a system that grow by demand and learn with his own history, ensures that the management of processing capacity is no more a (humans) system administrations but a system function, the tissue should be able to detect and react or forecast and prevent processing shortage and processing wastage situations.
Using this approach for system paradigm is feasible use big datacenters and rent resources for many tissues that coexists time-sharing resources as needed. Some classical cases that this is very useful are season changing behaviors like hotel systems and commerce system just before Christmas. Or some "sun following" systems that have more usage while this in its timezone and less while night.
The key features to solve this question are service migration, service scaling and service high availability in the tissue.
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