2015
DOI: 10.1145/2700321
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Engineering Pervasive Service Ecosystems

Abstract: Emerging pervasive computing services will typically involve a large number of devices and service components cooperating together in an open and dynamic environment. This calls for suitable models and infrastructures promoting spontaneous, situated, and self-adaptive interactions between components. SAPERE (Self-Aware Pervasive Service Ecosystems) is a general coordination framework aimed at facilitating the decentralized and situated execution of self-organizing and self-adaptive pervasive computing services… Show more

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Cited by 25 publications
(24 citation statements)
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“…• SAPERE [15][16][17][18][19][20] • CASCADAS [21][22][23] • BIONETS [24][25][26][27] • service reconfiguration for service ecosystems [80]. Figure 5 and Table 3 provide a comparison of these four primary methods.…”
Section: Ac Methods In Service Ecosystemsmentioning
confidence: 99%
See 3 more Smart Citations
“…• SAPERE [15][16][17][18][19][20] • CASCADAS [21][22][23] • BIONETS [24][25][26][27] • service reconfiguration for service ecosystems [80]. Figure 5 and Table 3 provide a comparison of these four primary methods.…”
Section: Ac Methods In Service Ecosystemsmentioning
confidence: 99%
“…In [15][16][17][18][19][20], the authors propose a nature-inspired reference architecture called SAPERE (Self-Aware Pervasive Service Ecosystems), which can be a useful guide in the design and implementation of self-adaptive pervasive service ecosystems. They identify several research challenges emerging from the convergence of cyber-physical worlds, such as comprehensive situation-awareness, top-down vs. bottom-up design, power of masses, decentralized control, and diversity and evolvability [19].…”
Section: Saperementioning
confidence: 99%
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“…In their work (Cabri et al, 2016), they explored how services can be composed in a user-aware way. To this purpose, they rely on the SAPERE middleware infrastructure (Castelli et al, 2015), which enables a dynamic and adaptive composition of services based on flexible nature-inspired rules. In their late work Cabri et al (Cabri2 et al, 2016) proposed to extend the previous approach by considering also semantic techniques and simple collaboration aspects.…”
Section: Related Workmentioning
confidence: 99%