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Network slicing might radically change the relations among different actors of the telecommunications ecosystem, where new players, active in different markets, could benefit of tailored connectivity services based on different business strategies. We argue that for fully exploiting the opportunities offered by network slicing, dynamic sharing of resources is crucial not only for efficiency and cost savings, but also for enabling a resource negotiation that can unleash the potential of new business relations. We develop an automated mechanism that allows tenants to take strategic decisions to optimize the management of their slices based on their instantaneous demands and model their interaction as in marketplace. We integrate our solution, based on game theory, on a 3GPP calibrated system level simulator, where a slice-aware scheduler enforces the tenants’ decisions at the Nash Equilibrium (NE). We compare our proposal with a static baseline, that assigns a fixed share of resources to each slice, and show that, by dynamically trading resources in the market, tenants achieve lower costs, and, therefore, higher profits. We provide an algorithmic implementation that guarantees the convergence to a single NE and test the computational complexity of our algorithm to an increasing number of slices in the system. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to compare VVI, VVIR and DDD modes in patients with indication to dual-chamber stimulation, depending on left ventricular function., Methods: Two groups of patients were implanted with a DDD pacemaker: Group I with ejection fraction > 40% and Group II with ejection fraction < 40%. Patients with a history of atrial arrhythmia or retrograde conduction were excluded. At follow-up (1 month each) quality of life (QoL), patient preference and echo parameters were collected. At hospital discharge all patients were programmed in DDD for 1 month and then randomized to VVI or VVIR mode. At the end of the period in VVI or VVIR mode each patient underwent a control period in DDD and then was programmed in VVIR or VVI mode., Results: Seventeen patients out of 23 preferred DDD mode and 6 did not perceive any subjective difference among DDD, VVI and VVIR modes (4/9 in Group I and 2/14 in Group II, p = 0.0017). QoL was significantly different between the two groups and at each follow-up showed the best values in DDD. The correlation between QoL and Tei index was 0.62 in Group I (p < 0.001) and 0.35 in Group II (p = 0.001). Neither ejection fraction nor fractional shortening showed any significant difference during the three phases of the study., Conclusions: Most patients preferred the DDD mode. The Tei index showed a good correlation with QoL and both QoL and Tei index significantly improved with DDD mode as compared to VVI and VVIR.