Min-energy voltage allocation for tree-structured tasks

We study job scheduling on processors capable of running at variable voltage/speed to minimize energy consumption. Each job in a problem instance is specified by its arrival time and deadline, together with required number of CPU cycles. It is known that the minimum energy schedule for n jobs can be computed in O(n³) time, assuming a convex energy function. We investigate more efficient algorithms for computing the optimal schedule when the job sets have certain special structures. When the time intervals are structured as trees, the minimum energy schedule is shown to have a succinct characterization and is computable in time O(P) where P is the tree’s total path length. We also study an on-line average-rate heuristics AVR and prove that its energy consumption achieves a small constant competitive ratio for nested job sets and for job sets with limited overlap. Some simulation results are also given. This work is supported in part by Research Grants Council of Hong Kong under grant No. CityU 1165/04E, National Natural Science Foundation of China under Grant No. 60135010, 60321002 and the Chinese National Key Foundation Research & Development Plan (2004CB318108).     

Becoming Adult in America

Sociological Forum -     

Moving and Children's Social Connections: Neighborhood Context and the Consequences of Moving for Low-Income Families

Using data from an experimental housing relocation program, this research compares social connections of children in families that move with those of similar children who do not move. Qualitative interview data are used to examine what factors influence the formation of social connections after moving. Results show the impact of moving on children's social connections is influenced by neighborhood context, financial resources, and children's age at the time of the move. Studies of moving during childhood need to pay closer attention to the factors that influence where, when, and why families move.